open-notebook/docs/0-START-HERE/quick-start-openai.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

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4.3 KiB
Markdown

# Quick Start - OpenAI (5 minutes)
Get Open Notebook running with OpenAI's GPT models. Fast, powerful, and simple.
## Prerequisites
1. **Docker Desktop** installed
- [Download here](https://www.docker.com/products/docker-desktop/)
- Already have it? Skip to step 2
2. **OpenAI API Key** (required)
- Go to https://platform.openai.com/api-keys
- Create account → Create new secret key
- Add at least $5 in credits to your account
- Copy the key (starts with `sk-`)
## Step 1: Create Configuration (1 min)
Create a new folder `open-notebook` and add this file:
**docker-compose.yml**:
```yaml
services:
surrealdb:
image: surrealdb/surrealdb:v2
command: start --user root --pass password --bind 0.0.0.0:8000 rocksdb:/mydata/mydatabase.db
ports:
- "8000:8000"
volumes:
- ./surreal_data:/mydata
open_notebook:
image: lfnovo/open_notebook:v1-latest
pull_policy: always
ports:
- "8502:8502" # Web UI
- "5055:5055" # API
environment:
# Encryption key for credential storage (required)
- OPEN_NOTEBOOK_ENCRYPTION_KEY=change-me-to-a-secret-string
# Database (required)
- SURREAL_URL=ws://surrealdb:8000/rpc
- SURREAL_USER=root
- SURREAL_PASSWORD=password
- SURREAL_NAMESPACE=open_notebook
- SURREAL_DATABASE=open_notebook
volumes:
- ./notebook_data:/app/data
depends_on:
- surrealdb
restart: always
```
**Edit the file:**
- Replace `change-me-to-a-secret-string` with your own secret (any string works)
---
## Step 2: Start Services (1 min)
Open terminal in your `open-notebook` folder:
```bash
docker compose up -d
```
Wait 15-20 seconds for services to start.
---
## Step 3: Access Open Notebook (instant)
Open your browser:
```
http://localhost:8502
```
You should see the Open Notebook interface!
---
## Step 4: Configure Your OpenAI Provider (1 min)
1. Go to **Settings****API Keys**
2. Click **Add Credential**
3. Select provider: **OpenAI**
4. Give it a name (e.g., "My OpenAI Key")
5. Paste your OpenAI API key
6. Click **Save**
7. Click **Test Connection** — should show success
8. Click **Discover Models****Register Models**
Your OpenAI models are now available!
---
## Step 5: Create Your First Notebook (1 min)
1. Click **New Notebook**
2. Name: "My Research"
3. Click **Create**
---
## Step 6: Add a Source (1 min)
1. Click **Add Source**
2. Choose **Web Link**
3. Paste: `https://en.wikipedia.org/wiki/Artificial_intelligence`
4. Click **Add**
5. Wait for processing (30-60 seconds)
---
## Step 7: Chat With Your Content (1 min)
1. Go to **Chat**
2. Type: "What is artificial intelligence?"
3. Click **Send**
4. Watch as GPT responds with information from your source!
---
## Verification Checklist
- [ ] Docker is running
- [ ] You can access `http://localhost:8502`
- [ ] OpenAI credential is configured and tested
- [ ] You created a notebook
- [ ] You added a source
- [ ] Chat works
**All checked?** You have a fully working AI research assistant!
---
## Using Different Models
In your notebook, go to **Settings****Models** to choose:
- `gpt-4o` - Best quality (recommended)
- `gpt-4o-mini` - Fast and cheap (good for testing)
---
## Troubleshooting
### "Port 8502 already in use"
Change the port in docker-compose.yml:
```yaml
ports:
- "8503:8502" # Use 8503 instead
```
Then access at `http://localhost:8503`
### "API key not working"
1. Go to **Settings****API Keys**
2. Click **Test Connection** on your OpenAI credential
3. If it fails, verify your key at https://platform.openai.com
4. Delete the credential and create a new one with the correct key
### "Cannot connect to server"
```bash
docker ps # Check all services running
docker compose logs # View logs
docker compose restart # Restart everything
```
---
## Next Steps
1. **Add Your Own Content**: PDFs, web links, documents
2. **Explore Features**: Podcasts, transformations, search
3. **Full Documentation**: [See all features](../3-USER-GUIDE/index.md)
---
## Cost Estimate
OpenAI pricing (approximate):
- **Conversation**: $0.01-0.10 per 1K tokens
- **Embeddings**: $0.02 per 1M tokens
- **Typical usage**: $1-5/month for light use, $20-50/month for heavy use
Check https://openai.com/pricing for current rates.
---
**Need help?** Join our [Discord community](https://discord.gg/37XJPXfz2w)!