open-notebook/docs/3-USER-GUIDE/api-configuration.md
Luis Novo 3f352cfcce
feat: credential-based API key management (#477) (#540)
* feat: replace provider config with credential-based system (#477)

Introduce a new credential management system replacing the old
ProviderConfig singleton and standalone Models page. Each credential
stores encrypted API keys and provider-specific configuration with
full CRUD support via a unified settings UI.

Backend:
- Add Credential domain model with encrypted API key storage
- Add credentials API router (CRUD, discovery, registration, testing)
- Add encryption utilities for secure key storage
- Add key_provider for DB-first env-var fallback provisioning
- Add connection tester and model discovery services
- Integrate ModelManager with credential-based config
- Add provider name normalization for Esperanto compatibility
- Add database migrations 11-12 for credential schema

Frontend:
- Rewrite settings/api-keys page with credential management UI
- Add model discovery dialog with search and custom model support
- Add compact default model assignments (primary/advanced layout)
- Add inline model testing and credential connection testing
- Add env-var migration banner
- Update navigation to unified settings page
- Remove standalone models page and old settings components

i18n:
- Update all 7 locale files with credential and model management keys

Closes #477

Co-Authored-By: JFMD <git@jfmd.us>
Co-Authored-By: OraCatQAQ <570768706@qq.com>

* fix: address PR #540 review comments

- Fix docs referencing removed Models page
- Fix error-handler returning raw messages instead of i18n keys
- Fix auth.py misleading docstring and missing no-password guard
- Fix connection_tester using wrong env var for openai_compatible
- Add provision_provider_keys before model discovery/sync
- Update CLAUDE.md to reflect credential-based system
- Fix missing closing brace in api-keys page useEffect

* fix: add logging to credential migration and surface errors in UI

- Add comprehensive logging to migrate-from-env and
  migrate-from-provider-config endpoints (start, per-provider
  progress, success/failure with stack traces, final summary)
- Fix frontend migration hooks ignoring errors array from response
- Show error toast when migration fails instead of "nothing to migrate"
- Invalidate status/envStatus queries after migration so banner updates

* docs: update CLAUDE.md files for credential system

Replace stale ProviderConfig and /api-keys/ references across 8 CLAUDE.md
files to reflect the new Credential-based system from PR #540.

* docs: update user documentation for credential-based system

Replace env var API key instructions with Settings UI credential
workflow across all user-facing documentation. The new flow is:
set OPEN_NOTEBOOK_ENCRYPTION_KEY → start services → add credential
in Settings UI → test → discover models → register.

- Rewrite ai-providers.md, api-configuration.md, environment-reference.md
- Update all quick-start guides and installation docs
- Update ollama.md, openai-compatible.md, local-tts/stt networking sections
- Update reverse-proxy.md, development-setup.md, security.md
- Fix broken links to non-existent docs/deployment/ paths
- Add credentials endpoints to api-reference.md
- Move all API key env vars to deprecated/legacy sections

* chore: bump version to 1.7.0-rc1

Release candidate for credential-based provider management system.

* fix: initialize provider before try block in test_credential

Prevents UnboundLocalError when Credential.get() throws (e.g.,
invalid credential_id) before provider is assigned.

* fix: reorder down migration to drop index before table

Removes duplicate REMOVE FIELD statement and reorders so the index
is dropped before the table, preventing rollback failures.

* refactor: simplify encryption key to always derive via SHA-256

Remove the dual code path in _ensure_fernet_key() that detected native
Fernet keys. Since the credential system is new, always deriving via
SHA-256 removes unnecessary complexity. Also removes the generate_key()
function and Fernet.generate_key() references from docs.

* fix: correct mock patch targets in embedding tests and URL validation

Fix embedding tests patching wrong module path for model_manager
(was targeting open_notebook.utils.embedding.model_manager but it's
imported locally from open_notebook.ai.models). Also fix URL validation
to allow unresolvable hostnames since they may be valid in the
deployment environment (e.g., Azure endpoints, internal DNS).

* feat: add global setup banner for encryption and migration status

Show a persistent banner in AppShell when encryption key is missing
(red) or env var API keys can be migrated (amber), so users see
these prompts on every page instead of only on Settings > API Keys.

Includes a docs link for the encryption banner and i18n support
across all 7 locales.

* docs: several improvements to docker-compose e env examples

* Update README.md

Co-authored-by: cubic-dev-ai[bot] <191113872+cubic-dev-ai[bot]@users.noreply.github.com>

* docs: fix env var format in README and update model setup instructions

Align the encryption key snippet in README Step 2 with the list
format used in the compose file. Replace deprecated "Settings →
Models" instructions with credential-based Discover Models flow.

* fix: address credential system review issues

- Fix SSRF bypass via IPv4-mapped IPv6 addresses (::ffff:169.254.x.x)
- Fix TTS connection test missing config parameter
- Add Azure-specific model discovery using api-key auth header
- Add Vertex static model list for credential-based discovery
- Fix PROVIDER_DISCOVERY_FUNCTIONS incorrect azure/vertex mapping
- Extract business logic to api/credentials_service.py (service layer)
- Move credential Pydantic schemas to api/models.py
- Update tests to use new service imports and ValueError assertions

* fix: sanitize error responses and migrate key_provider to Credential

- Replace raw exception messages in all credential router 500 responses
  with generic error strings (internal details logged server-side only)
- Refactor key_provider.py to use Credential.get_by_provider() instead
  of deprecated ProviderConfig.get_instance()
- Remove unused functions (get_provider_configs, get_default_api_key,
  get_provider_config) that were dead code

---------

Co-authored-by: JFMD <git@jfmd.us>
Co-authored-by: OraCatQAQ <570768706@qq.com>
2026-02-10 08:30:22 -03:00

11 KiB

API Configuration

Configure AI provider credentials through the Settings UI. No file editing required.

Credential System: Open Notebook uses encrypted credentials stored in the database. Each credential connects to a provider and allows you to discover, register, and test models.


Overview

Open Notebook manages AI provider access through a credential-based system:

  1. You create a credential for each provider (API key + settings)
  2. Credentials are encrypted and stored in the database
  3. You test connections to verify credentials work
  4. You discover and register models from each credential
  5. Models are linked to credentials for direct configuration

Encryption Setup

Before storing credentials, you must configure an encryption key.

Setting the Encryption Key

Add OPEN_NOTEBOOK_ENCRYPTION_KEY to your docker-compose.yml:

environment:
  - OPEN_NOTEBOOK_ENCRYPTION_KEY=my-secret-passphrase

Any string works as a key — it will be securely derived via SHA-256 internally.

Warning

: If you change or lose the encryption key, all stored credentials become unreadable. Back up your encryption key securely and separately from your database backups.

Docker Secrets Support

Both password and encryption key support Docker secrets:

# docker-compose.yml
services:
  open_notebook:
    environment:
      - OPEN_NOTEBOOK_PASSWORD_FILE=/run/secrets/app_password
      - OPEN_NOTEBOOK_ENCRYPTION_KEY_FILE=/run/secrets/encryption_key
    secrets:
      - app_password
      - encryption_key

secrets:
  app_password:
    file: ./secrets/password.txt
  encryption_key:
    file: ./secrets/encryption_key.txt

Encryption Details

API keys stored in the database are encrypted using Fernet (AES-128-CBC + HMAC-SHA256).

Configuration Behavior
Encryption key set Keys encrypted with your key
No encryption key set Storing credentials is disabled

Accessing Credential Configuration

  1. Click Settings in the navigation bar
  2. Select API Keys tab
  3. You'll see existing credentials and an Add Credential button
Navigation: Settings → API Keys

Supported Providers

Cloud Providers

Provider Required Fields Optional Fields
OpenAI API Key
Anthropic API Key
Google Gemini API Key
Groq API Key
Mistral API Key
DeepSeek API Key
xAI API Key
OpenRouter API Key
Voyage AI API Key
ElevenLabs API Key

Local/Self-Hosted

Provider Required Fields Notes
Ollama Base URL Typically http://localhost:11434 or http://ollama:11434

Enterprise

Provider Required Fields Optional Fields
Azure OpenAI API Key, Endpoint, API Version Service-specific endpoints (LLM, Embedding, STT, TTS)
OpenAI-Compatible Base URL API Key, Service-specific configs
Vertex AI Project ID, Location, Credentials Path

Creating a Credential

Step 1: Add Credential

  1. Go to SettingsAPI Keys
  2. Click Add Credential
  3. Select your provider
  4. Give it a descriptive name (e.g., "My OpenAI Key", "Work Anthropic")
  5. Fill in the required fields (API key, base URL, etc.)
  6. Click Save

Step 2: Test Connection

  1. On your new credential card, click Test Connection
  2. Wait for the result:
Result Meaning
Success Key is valid, provider accessible
Invalid API key Check key format and value
Connection failed Check URL, network, firewall

Step 3: Discover Models

  1. Click Discover Models on the credential card
  2. The system queries the provider for available models
  3. Review the discovered models

Step 4: Register Models

  1. Select the models you want to use
  2. Click Register Models
  3. The models are now available throughout Open Notebook

Multi-Credential Support

Each provider can have multiple credentials. This is useful when:

  • You have different API keys for different projects
  • You want to test with different endpoints
  • Multiple team members need separate credentials

Creating Multiple Credentials

  1. Click Add Credential again
  2. Select the same provider
  3. Fill in different credentials
  4. Each credential can discover and register its own models

When you register models from a credential, those models are linked to that specific credential. This means:

  • Each model knows which API key to use
  • You can have models from different credentials for the same provider
  • Deleting a credential removes its linked models

Testing Connections

Click Test Connection to verify your credential:

Result Meaning
Success Key is valid, provider accessible
Invalid API key Check key format and value
Connection failed Check URL, network, firewall
Model not available Key valid but model access restricted

Test uses inexpensive models (e.g., gpt-3.5-turbo, claude-3-haiku) to minimize cost.


Configuring Specific Providers

Simple Providers (API Key Only)

For OpenAI, Anthropic, Google, Groq, Mistral, DeepSeek, xAI, OpenRouter:

  1. Add credential with your API key
  2. Test connection
  3. Discover and register models

Ollama (URL-Based)

  1. Add credential with provider Ollama
  2. Enter the base URL (e.g., http://ollama:11434)
  3. Test connection
  4. Discover and register models

Ollama allows localhost and private IPs since it runs locally.

Azure OpenAI

Azure requires multiple fields:

Field Example Required
API Key abc123... Yes
Endpoint https://myresource.openai.azure.com Yes
API Version 2024-02-15-preview Yes
LLM Endpoint https://myresource-llm.openai.azure.com No
Embedding Endpoint https://myresource-embed.openai.azure.com No

Service-specific endpoints override the main endpoint for that service type.

OpenAI-Compatible

For custom OpenAI-compatible servers (LM Studio, vLLM, etc.):

  1. Add credential with provider OpenAI-Compatible
  2. Enter the base URL
  3. Enter API key (if required)
  4. Optionally configure per-service URLs

Supports separate configurations for:

  • LLM (language models)
  • Embedding
  • STT (speech-to-text)
  • TTS (text-to-speech)

Vertex AI

Google Cloud's enterprise AI platform:

Field Example
Project ID my-gcp-project
Location us-central1
Credentials Path /path/to/service-account.json

Migrating from Environment Variables

If you have existing API keys in environment variables (from a previous version):

  1. Open Settings → API Keys
  2. A banner appears: "Environment variables detected"
  3. Click Migrate to Database
  4. Keys are copied to the database (encrypted)
  5. Original environment variables remain unchanged

Migration Behavior

Scenario Action
Key in env only Migrated to database
Key in database only No change
Key in both Database version kept (skipped)

After Migration

  • Database credentials are used for all operations
  • You can remove the API key environment variables from your docker-compose.yml
  • Keep OPEN_NOTEBOOK_ENCRYPTION_KEY — it's still required

Migration Banner Visibility

The migration banner only appears when:

  • You have environment variables configured
  • Those providers are not already in the database
  • If all env providers are already migrated, the banner won't show

Migrating from ProviderConfig (v1.1 → v1.2)

If you're upgrading from an older version that used the ProviderConfig system:

  • The migration happens automatically on first startup
  • Your existing configurations are converted to credentials
  • Check Settings → API Keys to verify the migration succeeded
  • If you see issues, check the API logs for migration messages

Key Storage Security

Encryption

API keys stored in the database are encrypted using Fernet (AES-128-CBC + HMAC-SHA256).

Configuration Behavior
Encryption key set Keys encrypted with your key
No encryption key set Storing API keys in database is disabled

Default Credentials

Setting Default Value Production Recommendation
Password open-notebook-change-me Set OPEN_NOTEBOOK_PASSWORD
Encryption Key None (must be set) Set OPEN_NOTEBOOK_ENCRYPTION_KEY to any secret string

For production deployments, always set custom credentials.


Deleting Credentials

  1. Click the Delete button on the credential card
  2. Confirm deletion
  3. Credential and all its linked models are removed from the database

Troubleshooting

Credential Not Saving

Symptom Cause Solution
Save button disabled Empty or invalid input Enter a valid key
Error on save Encryption key not set Set OPEN_NOTEBOOK_ENCRYPTION_KEY in docker-compose.yml
Error on save Database connection issue Check database status

Test Connection Fails

Error Cause Solution
Invalid API key Wrong key or format Verify key from provider dashboard
Connection refused Wrong URL Check base URL format
Timeout Network issue Check firewall, proxy settings
403 Forbidden IP restriction Whitelist your server IP

Migration Issues

Problem Solution
No migration banner No env vars detected, or already migrated
Partial migration Check error list, fix and retry
Keys not working after migration Clear browser cache, restart services

Provider Shows "Not Configured"

  1. Check if a credential exists for this provider (Settings → API Keys)
  2. Test the credential connection
  3. Verify key format matches provider requirements
  4. Re-discover and register models if needed

Provider-Specific Notes

OpenAI

  • Keys start with sk-proj- (project keys) or sk- (legacy)
  • Requires billing enabled on account

Anthropic

  • Keys start with sk-ant-
  • Check account has API access enabled

Google Gemini

  • Keys start with AIzaSy
  • Free tier has rate limits

Ollama

  • No API key required
  • Default URL: http://localhost:11434 (local) or http://ollama:11434 (Docker)
  • Ensure Ollama server is running

Azure OpenAI

  • Endpoint format: https://{resource-name}.openai.azure.com
  • API version format: YYYY-MM-DD or YYYY-MM-DD-preview
  • Deployment names configured separately when registering models via the credential's Discover Models dialog