open-notebook/api/credentials_service.py
Matt Van Horn 95a6453009
feat: add anthropic_compatible credential provider (#1043)
Register anthropic_compatible in the provider registry so its env config,
modalities, test model, and /api/providers entry are derived from PROVIDERS
(#1075's single source of truth); the only manual copy is the SupportedProvider
Literal. Maps to esperanto's anthropic provider with a custom base_url, and
re-injects that base_url via ChatAnthropic since esperanto's to_langchain drops
it. Connection-test and model discovery mirror the openai_compatible siblings,
including DNS-rebinding pinning (prepare_pinned_http_target). A single shared
validator enforces the base_url + api_key requirement on both the create and
update paths.

Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com>
Co-authored-by: Luis Novo <lfnovo@gmail.com>
2026-07-19 15:14:17 -03:00

950 lines
35 KiB
Python

"""
Credentials Service
Business logic for managing AI provider credentials.
Extracted from the credentials router to follow the service layer pattern.
All functions raise ValueError for business errors (router converts to HTTPException).
"""
import os
from typing import Dict, List
import httpx
from loguru import logger
from pydantic import SecretStr
from api.models import CredentialResponse, validate_url_key_provider_required_fields
from open_notebook.ai.connection_tester import normalize_anthropic_compatible_base_url
from open_notebook.ai.model_discovery import (
ANTHROPIC_FALLBACK_MODELS,
OPENROUTER_AUDIO_MODELS,
classify_model_type,
fetch_anthropic_model_ids,
)
from open_notebook.ai.provider_registry import PROVIDERS
from open_notebook.domain.credential import Credential
from open_notebook.utils.encryption import get_secret_from_env
from open_notebook.utils.url_validation import (
prepare_pinned_http_target,
)
from open_notebook.utils.url_validation import (
validate_url as validate_url, # re-export for routers
)
# =============================================================================
# Constants
# =============================================================================
# Provider environment variable configuration, derived from the provider
# registry (open_notebook/ai/provider_registry.py — the source of truth).
# - "required": ALL listed env vars must be set for the provider to be considered configured.
# - "required_any": at least ONE of the listed env vars must be set.
# - "optional": additional env vars used during migration but not required.
PROVIDER_ENV_CONFIG: Dict[str, dict] = {
name: spec.env_config() for name, spec in PROVIDERS.items()
}
PROVIDER_MODALITIES: Dict[str, List[str]] = {
name: list(spec.modalities) for name, spec in PROVIDERS.items()
}
# =============================================================================
# Helpers
# =============================================================================
def require_encryption_key() -> None:
"""Raise ValueError if encryption key is not configured."""
if not get_secret_from_env("OPEN_NOTEBOOK_ENCRYPTION_KEY"):
raise ValueError(
"Encryption key not configured. "
"Set OPEN_NOTEBOOK_ENCRYPTION_KEY to enable storing API keys."
)
def credential_to_response(cred: Credential, model_count: int = 0) -> CredentialResponse:
"""Convert a Credential domain object to API response."""
return CredentialResponse(
id=cred.id or "",
name=cred.name,
provider=cred.provider,
modalities=cred.modalities,
base_url=cred.base_url,
endpoint=cred.endpoint,
api_version=cred.api_version,
endpoint_llm=cred.endpoint_llm,
endpoint_embedding=cred.endpoint_embedding,
endpoint_stt=cred.endpoint_stt,
endpoint_tts=cred.endpoint_tts,
project=cred.project,
location=cred.location,
credentials_path=cred.credentials_path,
num_ctx=cred.num_ctx,
has_api_key=cred.api_key is not None,
created=str(cred.created) if cred.created else "",
updated=str(cred.updated) if cred.updated else "",
model_count=model_count,
decryption_error=cred.decryption_error,
)
def check_env_configured(provider: str) -> bool:
"""Check if a provider has sufficient env vars configured for migration."""
config = PROVIDER_ENV_CONFIG.get(provider)
if not config:
return False
if "required_any" in config:
return any(bool(os.environ.get(v, "").strip()) for v in config["required_any"])
elif "required" in config:
return all(bool(os.environ.get(v, "").strip()) for v in config["required"])
return False
def get_default_modalities(provider: str) -> List[str]:
"""Get default modalities for a provider."""
return PROVIDER_MODALITIES.get(provider.lower(), ["language"])
def ensure_provider_required_fields(cred: Credential) -> None:
"""Validate provider-specific required fields on a merged credential before
save (update path). Delegates to the shared rule in api.models so the create
and update paths cannot drift."""
api_key = cred.api_key.get_secret_value() if cred.api_key else None
validate_url_key_provider_required_fields(cred.provider, cred.base_url, api_key)
def create_credential_from_env(provider: str) -> Credential:
"""Create a Credential from environment variables for a given provider."""
modalities = get_default_modalities(provider)
name = "Default (Migrated from env)"
if provider == "ollama":
return Credential(
name=name,
provider=provider,
modalities=modalities,
base_url=os.environ.get("OLLAMA_API_BASE"),
)
elif provider == "omlx":
api_key = os.environ.get("OMLX_API_KEY")
return Credential(
name=name,
provider=provider,
modalities=modalities,
api_key=SecretStr(api_key) if api_key else None,
base_url=os.environ.get("OMLX_API_BASE"),
)
elif provider == "vertex":
return Credential(
name=name,
provider=provider,
modalities=modalities,
project=os.environ.get("VERTEX_PROJECT"),
location=os.environ.get("VERTEX_LOCATION"),
credentials_path=os.environ.get("GOOGLE_APPLICATION_CREDENTIALS"),
)
elif provider == "azure":
return Credential(
name=name,
provider=provider,
modalities=modalities,
api_key=SecretStr(os.environ["AZURE_OPENAI_API_KEY"]),
endpoint=os.environ.get("AZURE_OPENAI_ENDPOINT"),
api_version=os.environ.get("AZURE_OPENAI_API_VERSION"),
endpoint_llm=os.environ.get("AZURE_OPENAI_ENDPOINT_LLM"),
endpoint_embedding=os.environ.get("AZURE_OPENAI_ENDPOINT_EMBEDDING"),
endpoint_stt=os.environ.get("AZURE_OPENAI_ENDPOINT_STT"),
endpoint_tts=os.environ.get("AZURE_OPENAI_ENDPOINT_TTS"),
)
elif provider in ("openai_compatible", "anthropic_compatible"):
env_prefix = provider.upper()
api_key = os.environ.get(f"{env_prefix}_API_KEY")
return Credential(
name=name,
provider=provider,
modalities=modalities,
api_key=SecretStr(api_key) if api_key else None,
base_url=os.environ.get(f"{env_prefix}_BASE_URL"),
)
elif provider == "google":
# Support both GOOGLE_API_KEY and GEMINI_API_KEY (fallback)
api_key = os.environ.get("GOOGLE_API_KEY") or os.environ.get("GEMINI_API_KEY")
return Credential(
name=name,
provider=provider,
modalities=modalities,
api_key=SecretStr(api_key) if api_key else None,
)
else:
# Simple API key providers
config = PROVIDER_ENV_CONFIG.get(provider, {})
required = config.get("required", [])
env_var = required[0] if required else None
api_key = os.environ.get(env_var) if env_var else None
return Credential(
name=name,
provider=provider,
modalities=modalities,
api_key=SecretStr(api_key) if api_key else None,
)
# =============================================================================
# Service Functions
# =============================================================================
async def get_provider_status() -> dict:
"""
Get configuration status: encryption key status, and per-provider
configured/source information.
"""
encryption_configured = bool(get_secret_from_env("OPEN_NOTEBOOK_ENCRYPTION_KEY"))
configured: Dict[str, bool] = {}
source: Dict[str, str] = {}
for provider in PROVIDER_ENV_CONFIG:
env_configured = check_env_configured(provider)
try:
db_credentials = await Credential.get_by_provider(provider)
db_configured = len(db_credentials) > 0
except Exception:
db_configured = False
configured[provider] = db_configured or env_configured
if db_configured:
source[provider] = "database"
elif env_configured:
source[provider] = "environment"
else:
source[provider] = "none"
return {
"configured": configured,
"source": source,
"encryption_configured": encryption_configured,
}
async def get_env_status() -> Dict[str, bool]:
"""Check what's configured via environment variables."""
env_status: Dict[str, bool] = {}
for provider in PROVIDER_ENV_CONFIG:
env_status[provider] = check_env_configured(provider)
return env_status
async def test_credential(credential_id: str) -> dict:
"""
Test connection using a credential's configuration.
Returns dict with provider, success, message keys.
"""
provider = "unknown"
try:
cred = await Credential.get(credential_id)
config = cred.to_esperanto_config()
from open_notebook.ai.connection_tester import (
_is_vertex_credentials_file_error,
_test_anthropic_compatible_connection,
_test_azure_connection,
_test_ollama_connection,
_test_openai_compatible_connection,
classify_provider_test_error,
)
provider = cred.provider.lower()
# Handle special providers
if provider == "ollama":
base_url = config.get("base_url", "http://localhost:11434")
success, message = await _test_ollama_connection(base_url)
return {"provider": provider, "success": success, "message": message}
if provider == "openai_compatible":
base_url = config.get("base_url")
api_key = config.get("api_key")
if not base_url:
return {
"provider": provider,
"success": False,
"message": "No base URL configured",
}
success, message = await _test_openai_compatible_connection(
base_url, api_key
)
return {"provider": provider, "success": success, "message": message}
if provider == "anthropic_compatible":
base_url = config.get("base_url")
api_key = config.get("api_key")
if not base_url:
return {
"provider": provider,
"success": False,
"message": "No base URL configured",
}
success, message = await _test_anthropic_compatible_connection(
base_url, api_key
)
return {"provider": provider, "success": success, "message": message}
if provider == "omlx":
# Esperanto oMLX profile default; port 11435 avoids SurrealDB on 8000.
base_url = config.get("base_url") or "http://localhost:11435/v1"
api_key = config.get("api_key")
success, message = await _test_openai_compatible_connection(
base_url, api_key
)
return {"provider": provider, "success": success, "message": message}
if provider == "azure":
success, message = await _test_azure_connection(
endpoint=config.get("endpoint"),
api_key=config.get("api_key"),
api_version=config.get("api_version"),
)
return {"provider": provider, "success": success, "message": message}
# Standard provider: use Esperanto to create and test
from esperanto.factory import AIFactory
from open_notebook.ai.connection_tester import TEST_MODELS
if provider not in TEST_MODELS:
return {
"provider": provider,
"success": False,
"message": f"Unknown provider: {provider}",
}
test_model, test_type = TEST_MODELS[provider]
if not test_model:
return {
"provider": provider,
"success": False,
"message": f"No test model configured for {provider}",
}
if test_type == "language":
model = AIFactory.create_language(
model_name=test_model, provider=provider, config=config
)
lc_model = model.to_langchain()
await lc_model.ainvoke("Hi")
return {"provider": provider, "success": True, "message": "Connection successful"}
elif test_type == "embedding":
embedding_model = AIFactory.create_embedding(
model_name=test_model, provider=provider, config=config
)
await embedding_model.aembed(["test"])
return {"provider": provider, "success": True, "message": "Connection successful"}
elif test_type == "text_to_speech":
AIFactory.create_text_to_speech(model_name=test_model, provider=provider, config=config)
return {
"provider": provider,
"success": True,
"message": "Connection successful (key format valid)",
}
return {
"provider": provider,
"success": False,
"message": f"Unsupported test type: {test_type}",
}
except Exception as e:
if provider == "vertex" and _is_vertex_credentials_file_error(e):
logger.debug(f"Vertex credentials file error for credential {credential_id}: {e}")
return {
"provider": provider,
"success": False,
"message": "Invalid or inaccessible credentials file",
}
error_msg = str(e)
success, message = classify_provider_test_error(error_msg)
if not success:
logger.debug(f"Test connection error for credential {credential_id}: {e}")
return {"provider": provider, "success": success, "message": message}
async def discover_with_config(provider: str, config: dict) -> List[dict]:
"""
Discover models using explicit config instead of env vars.
Returns model names only — no type classification.
The user chooses the model type when registering.
"""
api_key = config.get("api_key")
base_url = config.get("base_url")
def models_endpoint(url: str) -> str:
trimmed = url.rstrip("/")
if trimmed.endswith("/models"):
return trimmed
return f"{trimmed}/models"
# Static model lists for providers without a listing API
STATIC_MODELS: Dict[str, List[str]] = {
"voyage": [
"voyage-3", "voyage-3-lite", "voyage-code-3",
"voyage-finance-2", "voyage-law-2", "voyage-multilingual-2",
],
"elevenlabs": [
"eleven_multilingual_v2", "eleven_turbo_v2_5",
"eleven_turbo_v2", "eleven_monolingual_v1",
"scribe_v1", # speech-to-text
],
"deepgram": [
# TTS (Aura) voices
"aura-2-thalia-en", "aura-2-andromeda-en", "aura-2-helena-en",
"aura-2-apollo-en", "aura-2-arcas-en", "aura-2-asteria-en",
"aura-2-athena-en", "aura-2-hera-en", "aura-2-hermes-en",
"aura-2-atlas-en",
# STT (Nova / Whisper) transcription models
"nova-3", "nova-2", "whisper-large", "whisper-medium",
"whisper-small", "whisper-base", "whisper-tiny",
],
}
if provider in STATIC_MODELS:
if not api_key and provider != "ollama":
return []
return [
{"name": m, "provider": provider}
for m in STATIC_MODELS[provider]
]
if provider == "anthropic":
if not api_key:
return []
try:
model_names = await fetch_anthropic_model_ids(api_key)
except Exception as e:
logger.warning(
f"Failed to discover Anthropic models, using static fallback: {e}"
)
model_names = list(ANTHROPIC_FALLBACK_MODELS)
return [{"name": m, "provider": "anthropic"} for m in model_names]
# API-based discovery URLs (OpenAI-style /models endpoints), from the registry
url_map = {
name: spec.openai_compat_discovery_url
for name, spec in PROVIDERS.items()
if spec.openai_compat_discovery_url
}
if provider == "ollama":
ollama_url = base_url or "http://localhost:11434"
try:
# Pin DNS at request time so httpx cannot re-resolve to a
# metadata address after validation (DNS rebinding TOCTOU).
target = await prepare_pinned_http_target(
f"{ollama_url.rstrip('/')}/api/tags", "ollama"
)
headers = dict(target.headers)
async with httpx.AsyncClient() as client:
response = await client.get(
target.url,
headers=headers,
timeout=10.0,
extensions=target.extensions,
)
response.raise_for_status()
data = response.json()
return [
{
"name": m.get("name", ""),
"provider": "ollama",
"model_type": classify_model_type(m.get("name", ""), "ollama"),
}
for m in data.get("models", [])
if m.get("name")
]
except Exception as e:
logger.warning(f"Failed to discover Ollama models: {e}")
return []
if provider == "openai_compatible":
if not base_url:
return []
try:
# Pin DNS at request time so httpx cannot re-resolve to a
# metadata address after validation (DNS rebinding TOCTOU).
target = await prepare_pinned_http_target(
models_endpoint(base_url), "openai_compatible"
)
headers = dict(target.headers)
if api_key:
headers["Authorization"] = f"Bearer {api_key}"
async with httpx.AsyncClient() as client:
response = await client.get(
target.url,
headers=headers,
timeout=30.0,
extensions=target.extensions,
)
response.raise_for_status()
data = response.json()
return [
{"name": m.get("id", ""), "provider": "openai_compatible"}
for m in data.get("data", [])
if m.get("id")
]
except Exception as e:
logger.warning(f"Failed to discover openai_compatible models: {e}")
return []
if provider == "anthropic_compatible":
if not base_url or not api_key:
return []
try:
normalized_base_url = normalize_anthropic_compatible_base_url(base_url)
models_url = f"{normalized_base_url}/models"
# Pin DNS at request time (DNS-rebinding TOCTOU), mirroring the
# openai_compatible discovery path above.
target = await prepare_pinned_http_target(
models_url, "anthropic_compatible"
)
headers = dict(target.headers)
headers["x-api-key"] = api_key
headers["anthropic-version"] = "2023-06-01"
async with httpx.AsyncClient() as client:
response = await client.get(
target.url,
headers=headers,
timeout=30.0,
extensions=target.extensions,
)
response.raise_for_status()
data = response.json()
return [
{"name": m.get("id", ""), "provider": "anthropic_compatible"}
for m in data.get("data", [])
if m.get("id")
]
except Exception as e:
logger.warning(f"Failed to discover anthropic_compatible models: {e}")
return []
if provider == "omlx":
omlx_url = base_url or "http://localhost:11435/v1"
try:
target = await prepare_pinned_http_target(
models_endpoint(omlx_url), "omlx"
)
headers = dict(target.headers)
if api_key:
headers["Authorization"] = f"Bearer {api_key}"
async with httpx.AsyncClient() as client:
response = await client.get(
target.url,
headers=headers,
timeout=30.0,
extensions=target.extensions,
)
response.raise_for_status()
data = response.json()
return [
{"name": m.get("id", ""), "provider": "omlx"}
for m in data.get("data", [])
if m.get("id")
]
except Exception as e:
logger.warning(f"Failed to discover omlx models: {e}")
return []
if provider == "azure":
endpoint = config.get("endpoint")
api_version = config.get("api_version", "2024-10-21")
if not endpoint or not api_key:
return []
try:
# Pin DNS at request time so httpx cannot re-resolve to a
# metadata address after validation (DNS rebinding TOCTOU).
url = f"{endpoint.rstrip('/')}/openai/models?api-version={api_version}"
target = await prepare_pinned_http_target(url, "azure")
headers = dict(target.headers)
headers["api-key"] = api_key
async with httpx.AsyncClient() as client:
response = await client.get(
target.url,
headers=headers,
timeout=30.0,
extensions=target.extensions,
)
response.raise_for_status()
data = response.json()
return [
{"name": m.get("id", ""), "provider": "azure"}
for m in data.get("data", [])
if m.get("id")
]
except Exception as e:
logger.warning(f"Failed to discover Azure models: {e}")
return []
if provider == "vertex":
# Vertex AI requires service-account OAuth2 for model listing.
# Return a curated static list of well-known Vertex models instead.
VERTEX_MODELS = [
"gemini-3.5-flash",
"gemini-2.5-flash",
"gemini-2.5-flash-lite",
"text-embedding-005",
]
return [{"name": m, "provider": "vertex"} for m in VERTEX_MODELS]
if provider == "google":
try:
headers = {"X-Goog-Api-Key": api_key} if api_key else {}
async with httpx.AsyncClient() as client:
response = await client.get(
"https://generativelanguage.googleapis.com/v1/models",
headers=headers,
timeout=30.0,
)
response.raise_for_status()
data = response.json()
return [
{
"name": model.get("name", "").replace("models/", ""),
"provider": "google",
"description": model.get("displayName"),
}
for model in data.get("models", [])
if model.get("name")
]
except Exception as e:
logger.warning(f"Failed to discover Google models: {e}")
return []
if provider == "cohere":
# Cohere is not OpenAI-compatible; use esperanto's bespoke discovery.
if not api_key:
return []
try:
import asyncio
from esperanto import AIFactory
models = await asyncio.to_thread(
AIFactory.get_provider_models, "cohere", api_key=api_key
)
return [
{"name": m.id, "provider": "cohere"}
for m in models
if m.type in ("language", "embedding")
]
except Exception as e:
logger.warning(f"Failed to discover Cohere models: {e}")
return []
# Standard OpenAI-style API discovery
discovery_url = url_map.get(provider)
user_supplied_url = False
if provider == "openai" and base_url:
discovery_url = models_endpoint(base_url)
user_supplied_url = True
if not discovery_url or not api_key:
return []
try:
headers = {"Authorization": f"Bearer {api_key}"}
if user_supplied_url:
# Pin DNS at request time so httpx cannot re-resolve a
# user-supplied host to a metadata address after validation
# (DNS rebinding TOCTOU) — mirrors the openai_compatible path.
target = await prepare_pinned_http_target(discovery_url, provider)
request_url = target.url
headers.update(target.headers)
extensions = target.extensions
else:
request_url = discovery_url
extensions = {}
async with httpx.AsyncClient() as client:
response = await client.get(
request_url,
headers=headers,
timeout=30.0,
extensions=extensions,
)
response.raise_for_status()
data = response.json()
discovered = [
{
"name": m.get("id", ""),
"provider": provider,
"description": m.get("name"),
}
for m in data.get("data", [])
if m.get("id")
]
# OpenRouter's /models listing does not reliably surface its TTS/STT
# catalog, so seed the audio model ids esperanto ships as defaults.
if provider == "openrouter":
seen = {m["name"] for m in discovered}
for names in OPENROUTER_AUDIO_MODELS.values():
for name in names:
if name not in seen:
discovered.append({"name": name, "provider": provider})
seen.add(name)
return discovered
except Exception as e:
logger.warning(f"Failed to discover {provider} models: {e}")
return []
async def register_models(credential_id: str, models_data: list) -> dict:
"""
Register discovered models and link them to a credential.
Args:
credential_id: The credential ID to link models to
models_data: List of dicts with name, provider, model_type
Returns:
dict with created and existing counts
"""
cred = await Credential.get(credential_id)
from open_notebook.ai.models import Model
from open_notebook.database.repository import repo_query
# Batch fetch existing models for this provider
existing_models = await repo_query(
"SELECT string::lowercase(name) as name, string::lowercase(type) as type FROM model "
"WHERE string::lowercase(provider) = $provider",
{"provider": cred.provider.lower()},
)
existing_keys = {(m["name"], m["type"]) for m in existing_models}
created = 0
existing = 0
for model_data in models_data:
key = (model_data.name.lower(), model_data.model_type.lower())
if key in existing_keys:
existing += 1
continue
new_model = Model(
name=model_data.name,
provider=model_data.provider or cred.provider,
type=model_data.model_type,
credential=cred.id,
)
await new_model.save()
created += 1
return {"created": created, "existing": existing}
async def migrate_from_provider_config() -> dict:
"""
Migrate existing ProviderConfig data to individual credential records.
Returns dict with message, migrated, skipped, errors.
"""
logger.info("=== Starting ProviderConfig migration ===")
require_encryption_key()
logger.info("Encryption key verified")
from open_notebook.domain.provider_config import ProviderConfig
config = await ProviderConfig.get_instance()
logger.info(
f"Found ProviderConfig with {len(config.credentials)} provider(s): "
f"{', '.join(config.credentials.keys())}"
)
migrated = []
skipped = []
errors = []
for provider, credentials_list in config.credentials.items():
for old_cred in credentials_list:
try:
# Check if a credential already exists for this provider with same name
existing = await Credential.get_by_provider(provider)
names = [c.name for c in existing]
if old_cred.name in names:
logger.info(
f"[{provider}/{old_cred.name}] Already exists in DB, skipping"
)
skipped.append(f"{provider}/{old_cred.name}")
continue
# Determine modalities from the provider type
modalities = get_default_modalities(provider)
logger.info(f"[{provider}/{old_cred.name}] Creating credential")
new_cred = Credential(
name=old_cred.name,
provider=provider,
modalities=modalities,
api_key=old_cred.api_key,
base_url=old_cred.base_url,
endpoint=old_cred.endpoint,
api_version=old_cred.api_version,
endpoint_llm=old_cred.endpoint_llm,
endpoint_embedding=old_cred.endpoint_embedding,
endpoint_stt=old_cred.endpoint_stt,
endpoint_tts=old_cred.endpoint_tts,
project=old_cred.project,
location=old_cred.location,
credentials_path=old_cred.credentials_path,
)
await new_cred.save()
logger.info(
f"[{provider}/{old_cred.name}] Credential saved (id={new_cred.id})"
)
# Link existing models for this provider to the new credential
from open_notebook.ai.models import Model
from open_notebook.database.repository import repo_query
provider_models = await repo_query(
"SELECT * FROM model WHERE string::lowercase(provider) = $provider AND credential IS NONE",
{"provider": provider.lower()},
)
if provider_models:
logger.info(
f"[{provider}/{old_cred.name}] Linking {len(provider_models)} "
f"unassigned model(s)"
)
for model_data in provider_models:
model = Model(**model_data)
model.credential = new_cred.id
await model.save()
migrated.append(f"{provider}/{old_cred.name}")
except Exception as e:
logger.error(
f"[{provider}/{old_cred.name}] Migration FAILED: "
f"{type(e).__name__}: {e}",
exc_info=True,
)
errors.append(f"{provider}/{old_cred.name}: {e}")
logger.info(
f"=== ProviderConfig migration complete === "
f"migrated={len(migrated)} skipped={len(skipped)} errors={len(errors)}"
)
if migrated:
logger.info(f" Migrated: {', '.join(migrated)}")
if skipped:
logger.info(f" Skipped: {', '.join(skipped)}")
if errors:
logger.error(f" Errors: {'; '.join(errors)}")
return {
"message": f"Migration complete. Migrated {len(migrated)} credentials.",
"migrated": migrated,
"skipped": skipped,
"errors": errors,
}
async def migrate_from_env() -> dict:
"""
Migrate API keys from environment variables to credential records.
Returns dict with message, migrated, skipped, not_configured, errors.
"""
logger.info("=== Starting environment variable migration ===")
logger.info(
f"Checking {len(PROVIDER_ENV_CONFIG)} providers: "
f"{', '.join(PROVIDER_ENV_CONFIG.keys())}"
)
require_encryption_key()
logger.info("Encryption key verified")
from open_notebook.ai.models import Model
from open_notebook.database.repository import repo_query
migrated = []
skipped = []
not_configured = []
errors = []
for provider in PROVIDER_ENV_CONFIG:
try:
if not check_env_configured(provider):
logger.debug(f"[{provider}] No env vars configured, skipping")
not_configured.append(provider)
continue
logger.info(f"[{provider}] Env vars detected, checking for existing credentials")
existing = await Credential.get_by_provider(provider)
if existing:
logger.info(
f"[{provider}] Already has {len(existing)} credential(s) in DB, skipping"
)
skipped.append(provider)
continue
logger.info(f"[{provider}] Creating credential from env vars")
cred = create_credential_from_env(provider)
await cred.save()
logger.info(f"[{provider}] Credential saved successfully (id={cred.id})")
# Link unassigned models to this credential
provider_models = await repo_query(
"SELECT * FROM model WHERE string::lowercase(provider) = $provider AND credential IS NONE",
{"provider": provider.lower()},
)
if provider_models:
logger.info(
f"[{provider}] Linking {len(provider_models)} unassigned model(s) "
f"to credential {cred.id}"
)
for model_data in provider_models:
model = Model(**model_data)
model.credential = cred.id
await model.save()
else:
logger.info(f"[{provider}] No unassigned models to link")
migrated.append(provider)
except Exception as e:
logger.error(
f"[{provider}] Migration FAILED: {type(e).__name__}: {e}",
exc_info=True,
)
errors.append(f"{provider}: {e}")
logger.info(
f"=== Environment variable migration complete === "
f"migrated={len(migrated)} skipped={len(skipped)} "
f"not_configured={len(not_configured)} errors={len(errors)}"
)
if migrated:
logger.info(f" Migrated: {', '.join(migrated)}")
if skipped:
logger.info(f" Skipped (already in DB): {', '.join(skipped)}")
if errors:
logger.error(f" Errors: {'; '.join(errors)}")
return {
"message": f"Migration complete. Migrated {len(migrated)} providers.",
"migrated": migrated,
"skipped": skipped,
"not_configured": not_configured,
"errors": errors,
}