unsloth/studio/backend/auth/storage.py
Daniel Han 9a261aec5f
Studio: Expose openai and anthropic compatible external API end points (#4956)
* Studio: add API key authentication for programmatic access

External users want to hit the Studio API (chat completions with tool
calling, training, export, etc.) without going through the browser
login flow. This adds sk-unsloth- prefixed API keys that work as a
drop-in replacement for JWTs in the Authorization: Bearer header.

Backend:
- New api_keys table in SQLite (storage.py)
- create/list/revoke/validate functions with SHA-256 hashed storage
- API key detection in _get_current_subject before the JWT path
- POST/GET/DELETE /api/auth/api-keys endpoints on the auth router

Frontend:
- /api-keys page with create form, one-time key reveal, keys table
- API Keys link in desktop and mobile navbar
- Route registered with requireAuth guard

Zero changes to any existing route handler -- every endpoint that uses
Depends(get_current_subject) automatically works with API keys.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Use actual origin in API key usage examples

The examples on /api-keys were hardcoded to localhost:8888 which is
wrong for remote users. Use window.location.origin so the examples
show the correct URL regardless of where the user is connecting from.

* Add `unsloth studio run` CLI command for one-liner model serving

Adds a `run` subcommand that starts Studio, loads a model, creates an
API key, and prints a ready-to-use curl command -- similar to
`ollama run` or `vllm serve`.

Usage: unsloth studio run -m unsloth/Qwen3-1.7B-GGUF --gguf-variant UD-Q4_K_XL

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Add end-to-end tests for `unsloth studio run` and API key usage

Tests the 4 usage examples from the API Keys page:
1. curl basic (non-streaming) chat completions
2. curl streaming (SSE) chat completions
3. OpenAI Python SDK streaming completions
4. curl with tools (web_search + python)

Also tests --help output, invalid key rejection, and no-key rejection.
All 7 tests pass against Qwen3-1.7B-GGUF.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Add /v1/completions, /v1/embeddings, /v1/responses endpoints and --parallel support

- llama_cpp.py: accept n_parallel param, pass to llama-server --parallel
- run.py: plumb llama_parallel_slots through to app.state
- inference.py: add /completions and /embeddings as transparent proxies to
  llama-server, add /responses as application-level endpoint that converts
  to ChatCompletionRequest; thread n_parallel through load_model
- studio.py: set llama_parallel_slots=4 for `unsloth studio run` path

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Make /v1/responses endpoint match OpenAI Responses API format

The existing /v1/responses shim returned Chat Completions format, which
broke OpenAI SDK clients using openai.responses.create(). This commit
replaces the endpoint with a proper implementation that:

- Returns `output` array with `output_text` content parts instead of
  `choices` with `message`
- Uses `input_tokens`/`output_tokens` instead of `prompt_tokens`/
  `completion_tokens` in usage
- Sets `object: "response"` and `id: "resp_..."`
- Emits named SSE events for streaming (response.created,
  response.output_text.delta, response.completed, etc.)
- Accepts all OpenAI Responses API fields (tools, store, metadata,
  previous_response_id) without erroring -- silently ignored
- Maps `developer` role to `system` and `input_text`/`input_image`
  content parts to the internal Chat format

Adds Pydantic schemas for request/response models and 23 unit tests
covering schema validation, input normalisation, and response format.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Studio: add Anthropic-compatible /v1/messages endpoint (#4981)

* Add Anthropic-compatible /v1/messages endpoint with tool support

Translate Anthropic Messages API format to/from internal OpenAI format
and reuse the existing server-side agentic tool loop. Supports streaming
SSE (message_start, content_block_delta, etc.) and non-streaming JSON.
Includes offline unit tests and e2e tests in test_studio_run.py.

* Add enable_tools, enabled_tools, session_id to /v1/messages endpoint

Support the same shorthand as /v1/chat/completions: enable_tools=true
with an optional enabled_tools list uses built-in server tools without
requiring full Anthropic tool definitions. session_id is passed through
for sandbox isolation. max_tokens is now optional.

* Strip leaked tool-call XML from Anthropic endpoint content

Apply _TOOL_XML_RE to content events in both streaming and
non-streaming tool paths, matching the OpenAI endpoint behavior.

* Emit custom tool_result SSE event in Anthropic stream

Adds a non-standard tool_result event between the tool_use block close
and the next text block, so clients can see server-side tool execution
results. Anthropic SDKs ignore unknown event types.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Split /v1/messages into server-side and client-side tool paths

enable_tools=true runs the existing server-side agentic loop with
built-in tools (web_search/python/terminal). A bare tools=[...] field
now triggers a client-side pass-through: client-provided tools are
forwarded to llama-server and any tool_use output is returned to the
caller with stop_reason=tool_use for client execution.

This fixes Claude Code (and any Anthropic SDK client) which sends
tools=[...] expecting client-side execution but was previously routed
through execute_tool() and failing with 'Unknown tool'.

Adds AnthropicPassthroughEmitter to convert llama-server OpenAI SSE
chunks into Anthropic SSE events, plus unit tests covering text
blocks, tool_use blocks, mixed, stop reasons, and usage.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Fix httpcore GeneratorExit in /v1/messages passthrough stream

Explicitly aclose aiter_lines() before the surrounding async with
blocks unwind, mirroring the prior fix in external_provider.py
(a41160d3) and cc757b78's RuntimeError suppression.

* Wire stop_sequences through /v1/messages; warn on tool_choice

Plumb payload.stop_sequences to all three code paths (server-side
tool loop, no-tool plain, client-side passthrough) so Anthropic SDK
clients setting stop_sequences get the behavior they expect. The
llama_cpp backend already accepted `stop` on both generate_chat_
completion and generate_chat_completion_with_tools; the Anthropic
handler simply wasn't passing it.

tool_choice remains declared on the request model for Anthropic SDK
compatibility (the SDK often sets it by default) but is not yet
honored. Log a structured warning on each request carrying a non-
null tool_choice so the silent drop is visible to operators.

* Wire min_p / repetition_penalty / presence_penalty through /v1/messages

Align the Anthropic endpoint's sampling surface with /v1/chat/completions.
Adds the three fields as x-unsloth extensions on AnthropicMessagesRequest
and threads them through all three code paths: server-side tool loop,
no-tool plain, and client-side passthrough.

The passthrough builder emits "repeat_penalty" (not "repetition_penalty")
because that is llama-server's field name; the backend methods already
apply the same rename internally.

* Fix block ordering and prev_text reset in non-streaming tool path

_anthropic_tool_non_streaming was building the response by appending
all tool_use blocks first, then a single concatenated text block at
the end — losing generation order and merging pre-tool and post-tool
text into one block. It also never reset prev_text between synthesis
turns, so the first N characters of each post-tool turn were dropped
(where N = length of the prior turn's final cumulative text).

Rewrite to build content_blocks incrementally in generation order,
matching the streaming emitter's behavior: deltas within a turn are
merged into the trailing text block, tool_use blocks interrupt the
text sequence, and prev_text is reset on tool_end so turn N+1 diffs
against an empty baseline.

Caught by gemini-code-assist[bot] review on #4981.

* Make test_studio_run.py e2e tests pytest-compatible

Add a hybrid session-scoped studio_server fixture in conftest.py that
feeds base_url / api_key into the existing e2e test functions. Three
invocation modes are now supported:

1. Script mode (unchanged) — python tests/test_studio_run.py
2. Pytest + external server — point at a running instance via
   UNSLOTH_E2E_BASE_URL / UNSLOTH_E2E_API_KEY env vars, no per-run
   GGUF load cost
3. Pytest + fixture-managed server — pytest drives _start_server /
   _kill_server itself via --unsloth-model / --unsloth-gguf-variant,
   CI-friendly

The existing _start_server / _kill_server helpers and main() stay
untouched so the script entry point keeps working exactly as before.
Test function signatures are unchanged — the (base_url, api_key)
parameters now resolve via the new fixtures when running under
pytest.

* Rename test_studio_run.py -> test_studio_api.py

The file is entirely about HTTP API endpoint testing (OpenAI-compatible
/v1/chat/completions, Anthropic-compatible /v1/messages, API key auth,
plus a CLI --help sanity check on the command that runs the API). None
of its tests cover training, export, chat-UI, or internal-Python-API
concerns.

The old name misleadingly suggested "tests for the unsloth studio run
CLI subcommand" — the new name reflects the actual scope.

Updates:
- git mv the file (rename tracked, history preserved)
- Rewrite opening docstring to state the API surface focus and call
  out what is explicitly out of scope
- Update all 4 Usage-block path references to the new filename
- LOG_FILE renamed to test_studio_api.log
- conftest.py fixture import rewritten from test_studio_run to
  test_studio_api, plus 7 docstring/comment references updated

No functional changes to test logic, signatures, or main().

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

* Fix httpcore asyncgen cleanup in /v1/messages and /v1/completions

The earlier fix in 985e92a9 was incomplete: it closed aiter_lines()
explicitly but still used `async with httpx.AsyncClient()` /
`async with client.stream()` inside the generator. When the generator
is orphaned (e.g. client disconnects mid-stream and Starlette drops
the StreamingResponse iterator without explicitly calling aclose()),
Python's asyncgen finalizer runs the cleanup in a DIFFERENT task than
the one that originally entered the httpx context managers. The
`async with` exits then trigger httpcore's HTTP11ConnectionByteStream
.aclose(), which enters anyio.CancelScope.__exit__ with a mismatched
task and raises RuntimeError("Attempted to exit cancel scope in a
different task"). That error escapes any user-owned try/except
because it happens during GC finalization.

Replace `async with` with manual client/response lifecycle in both
/v1/messages passthrough and /v1/completions proxy. Close the
response and client in a finally block wrapped in
`try: ... except Exception: pass`. This suppresses RuntimeError (and
other Exception subclasses) from the anyio cleanup noise while
letting GeneratorExit (a BaseException, not Exception) propagate
cleanly so the generator terminates as Python expects.

Traceback observed in user report:
  File ".../httpcore/_async/connection_pool.py", line 404, in __aiter__
      yield part
  RuntimeError: async generator ignored GeneratorExit
...
  File ".../anyio/_backends/_asyncio.py", line 455, in __exit__
      raise RuntimeError(
  RuntimeError: Attempted to exit cancel scope in a different task

* Expand unsloth studio run banner with SDK base URL and more curl examples

Add an explicit "OpenAI / Anthropic SDK base URL" line inside the info
box so SDK users don't accidentally copy the bare server URL (without
/v1) into their OpenAI/Anthropic SDK constructors and hit 404s.

Replace the single /v1/chat/completions curl example with three
labeled blocks: chat/completions, Anthropic /messages, and OpenAI
Responses. The Anthropic example includes max_tokens (Anthropic SDKs
require it even though Studio accepts None).

All examples derived from a computed sdk_base_url so the /v1 prefix
stays in sync if the public path ever changes.

* Hash API keys with HMAC-SHA256 + persistent server secret

Stores the HMAC secret in a new app_secrets singleton table. Fixes
CodeQL py/weak-sensitive-data-hashing alert on storage.py:74-76,
394-395. Refresh tokens stay on plain SHA-256 (unchanged _hash_token)
so existing user sessions survive upgrade — API keys are new on this
branch so there is no migration.

* Use PBKDF2 for API key hashing per CodeQL recommendation

HMAC-SHA256 was still flagged by py/weak-sensitive-data-hashing.
Switch to hashlib.pbkdf2_hmac, which is in CodeQL's recommended
allowlist (Argon2/scrypt/bcrypt/PBKDF2). Persistent server-side
salt stays in app_secrets for defense-in-depth. 100k iterations to
match auth/hashing.py's password hasher.

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
2026-04-13 21:08:11 +04:00

582 lines
18 KiB
Python

# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
"""
SQLite storage for authentication data (user credentials + JWT secret).
"""
import hashlib
import secrets
import sqlite3
from datetime import datetime, timezone
from typing import Optional, Tuple
from utils.paths import auth_db_path, ensure_dir
DB_PATH = auth_db_path()
DEFAULT_ADMIN_USERNAME = "unsloth"
# Plaintext bootstrap password file — lives beside auth.db, deleted on
# first password change so the credential never lingers on disk.
_BOOTSTRAP_PW_PATH = DB_PATH.parent / ".bootstrap_password"
# In-process cache so we don't re-read the file on every HTML serve.
_bootstrap_password: Optional[str] = None
def generate_bootstrap_password() -> str:
"""Generate a 4-word diceware passphrase and persist it to disk.
The passphrase is written to ``_BOOTSTRAP_PW_PATH`` so that it
survives server restarts (the DB only stores the *hash*). On
subsequent calls / restarts, the persisted value is returned.
"""
global _bootstrap_password
# 1. Already cached in this process?
if _bootstrap_password is not None:
return _bootstrap_password
# 2. Already persisted from a previous run?
if _BOOTSTRAP_PW_PATH.is_file():
_bootstrap_password = _BOOTSTRAP_PW_PATH.read_text().strip()
if _bootstrap_password:
return _bootstrap_password
# 3. First-ever startup — generate a fresh passphrase.
import diceware
_bootstrap_password = diceware.get_passphrase(
options = diceware.handle_options(args = ["-n", "4", "-d", "", "-c"])
)
# Persist so the *same* passphrase is used if the server restarts
# before the user changes the password.
ensure_dir(_BOOTSTRAP_PW_PATH.parent)
_BOOTSTRAP_PW_PATH.write_text(_bootstrap_password)
return _bootstrap_password
def get_bootstrap_password() -> Optional[str]:
"""Return the cached bootstrap password, or None if not yet generated."""
return _bootstrap_password
def clear_bootstrap_password() -> None:
"""Delete the persisted bootstrap password file (called after password change)."""
global _bootstrap_password
_bootstrap_password = None
if _BOOTSTRAP_PW_PATH.is_file():
_BOOTSTRAP_PW_PATH.unlink(missing_ok = True)
def _hash_token(token: str) -> str:
"""SHA-256 hash helper used for refresh token storage.
Plain SHA-256 is intentional here: refresh tokens are high-entropy
random strings from ``secrets.token_urlsafe(48)`` (384 bits of
entropy), so a slow KDF (Argon2 / bcrypt / PBKDF2) provides zero
additional security — no attacker can brute-force 2^384 regardless
of hash speed — while adding tens of ms of CPU to every refresh.
See the OWASP Password Storage Cheat Sheet on fast-vs-slow hashing
of high-entropy inputs.
API keys use the separate ``_pbkdf2_api_key`` helper below, which
runs PBKDF2-HMAC-SHA256 with a persistent server-side salt — not
for cryptographic reasons (128-bit random tokens don't need slow
hashing), but because CodeQL's ``py/weak-sensitive-data-hashing``
query mislabels API keys as passwords and demands a KDF.
"""
return hashlib.sha256(token.encode("utf-8")).hexdigest()
def get_connection() -> sqlite3.Connection:
"""Get a connection to the auth database, creating tables if needed."""
ensure_dir(DB_PATH.parent)
conn = sqlite3.connect(DB_PATH)
conn.row_factory = sqlite3.Row
conn.execute(
"""
CREATE TABLE IF NOT EXISTS auth_user (
id INTEGER PRIMARY KEY,
username TEXT UNIQUE NOT NULL,
password_salt TEXT NOT NULL,
password_hash TEXT NOT NULL,
jwt_secret TEXT NOT NULL,
must_change_password INTEGER NOT NULL DEFAULT 0
);
"""
)
conn.execute(
"""
CREATE TABLE IF NOT EXISTS refresh_tokens (
id INTEGER PRIMARY KEY,
token_hash TEXT NOT NULL,
username TEXT NOT NULL,
expires_at TEXT NOT NULL
);
"""
)
conn.execute(
"""
CREATE TABLE IF NOT EXISTS api_keys (
id INTEGER PRIMARY KEY AUTOINCREMENT,
username TEXT NOT NULL,
key_prefix TEXT NOT NULL,
key_hash TEXT NOT NULL UNIQUE,
name TEXT NOT NULL DEFAULT '',
created_at TEXT NOT NULL,
last_used_at TEXT,
expires_at TEXT,
is_active INTEGER NOT NULL DEFAULT 1
);
"""
)
conn.execute(
"""
CREATE TABLE IF NOT EXISTS app_secrets (
key TEXT PRIMARY KEY,
value TEXT NOT NULL
);
"""
)
columns = {row["name"] for row in conn.execute("PRAGMA table_info(auth_user)")}
if "must_change_password" not in columns:
conn.execute(
"ALTER TABLE auth_user ADD COLUMN must_change_password INTEGER NOT NULL DEFAULT 0"
)
conn.commit()
return conn
# ── API-key PBKDF2 salt ────────────────────────────────────────────────
#
# Module-level cache for the persistent API-key PBKDF2 salt. Populated
# lazily on first use via ``_get_or_create_api_key_pbkdf2_salt``. Not
# protected by a lock because (a) the ``INSERT OR IGNORE`` provides
# atomicity at the SQLite layer and (b) concurrent populations converge
# on the same value, so the worst case is a harmless duplicate read on
# startup.
_api_key_pbkdf2_salt_cache: Optional[bytes] = None
def _get_or_create_api_key_pbkdf2_salt() -> bytes:
"""Return the persistent API-key PBKDF2 salt, generating it once if missing.
Stored as a hex-encoded 32-byte random value in the ``app_secrets``
table under key ``"api_key_pbkdf2_salt"``. Regenerated only if the row
is missing (i.e. fresh install, or operator manually deleted the row
and accepts invalidating existing API keys).
"""
global _api_key_pbkdf2_salt_cache
if _api_key_pbkdf2_salt_cache is not None:
return _api_key_pbkdf2_salt_cache
conn = get_connection()
try:
cur = conn.execute(
"SELECT value FROM app_secrets WHERE key = ?",
("api_key_pbkdf2_salt",),
)
row = cur.fetchone()
if row is None:
new_value = secrets.token_hex(32) # 32 bytes -> 64 hex chars
conn.execute(
"INSERT OR IGNORE INTO app_secrets (key, value) VALUES (?, ?)",
("api_key_pbkdf2_salt", new_value),
)
conn.commit()
cur = conn.execute(
"SELECT value FROM app_secrets WHERE key = ?",
("api_key_pbkdf2_salt",),
)
row = cur.fetchone()
salt = bytes.fromhex(row["value"])
finally:
conn.close()
_api_key_pbkdf2_salt_cache = salt
return salt
_API_KEY_PBKDF2_ITERATIONS = 100_000
def _pbkdf2_api_key(raw_key: str) -> str:
"""PBKDF2-HMAC-SHA256 an API key with a persistent server-side salt.
Used for API-key storage ONLY, not refresh tokens. Matches the
PBKDF2 algorithm + iteration count used by the password hasher in
``auth/hashing.py`` so the codebase is consistent on which KDF it
uses for credential storage.
Notes on why a slow KDF here is *only* a CodeQL appeasement and
*not* a cryptographic requirement: API keys are cryptographically
random 128-bit tokens (via ``secrets.token_hex``), so brute force
against 2^128 is infeasible regardless of hash speed. CodeQL's
``py/weak-sensitive-data-hashing`` query mislabels these tokens as
"password" sensitive data and then demands a KDF from its
allowlist (Argon2 / scrypt / bcrypt / PBKDF2). Per the query's
own recommendation page we use PBKDF2. The persistent salt is
still loaded from ``app_secrets`` so an attacker dumping the
``api_keys`` table alone cannot derive hashes for candidate
tokens without also obtaining the salt row.
"""
salt = _get_or_create_api_key_pbkdf2_salt()
dk = hashlib.pbkdf2_hmac(
"sha256",
raw_key.encode("utf-8"),
salt,
_API_KEY_PBKDF2_ITERATIONS,
)
return dk.hex()
def is_initialized() -> bool:
"""Check if auth is ready for login (at least one user exists in DB)."""
conn = get_connection()
cur = conn.execute("SELECT COUNT(*) AS c FROM auth_user")
row = cur.fetchone()
conn.close()
return bool(row["c"])
def create_initial_user(
username: str,
password: str,
jwt_secret: str,
*,
must_change_password: bool = False,
) -> None:
"""
Create the initial admin user in the database.
Raises sqlite3.IntegrityError if username already exists.
"""
from .hashing import hash_password
salt, pwd_hash = hash_password(password)
conn = get_connection()
try:
conn.execute(
"""
INSERT INTO auth_user (
username,
password_salt,
password_hash,
jwt_secret,
must_change_password
)
VALUES (?, ?, ?, ?, ?)
""",
(username, salt, pwd_hash, jwt_secret, int(must_change_password)),
)
conn.commit()
finally:
conn.close()
def delete_user(username: str) -> None:
"""
Delete a user from the database.
Used for rollback when user creation fails partway through bootstrap.
"""
conn = get_connection()
try:
conn.execute("DELETE FROM auth_user WHERE username = ?", (username,))
conn.commit()
finally:
conn.close()
def get_user_and_secret(username: str) -> Optional[Tuple[str, str, str, bool]]:
"""
Get user's password salt, hash, and JWT secret.
Returns (password_salt, password_hash, jwt_secret, must_change_password)
or None if user not found.
"""
conn = get_connection()
try:
cur = conn.execute(
"""
SELECT password_salt, password_hash, jwt_secret, must_change_password
FROM auth_user
WHERE username = ?
""",
(username,),
)
row = cur.fetchone()
if not row:
return None
return (
row["password_salt"],
row["password_hash"],
row["jwt_secret"],
bool(row["must_change_password"]),
)
finally:
conn.close()
def get_jwt_secret(username: str) -> Optional[str]:
"""Return the current JWT signing secret for a user."""
conn = get_connection()
try:
cur = conn.execute(
"SELECT jwt_secret FROM auth_user WHERE username = ?",
(username,),
)
row = cur.fetchone()
return row["jwt_secret"] if row else None
finally:
conn.close()
def requires_password_change(username: str) -> bool:
"""Return whether the user must change the seeded default password."""
conn = get_connection()
try:
cur = conn.execute(
"SELECT must_change_password FROM auth_user WHERE username = ?",
(username,),
)
row = cur.fetchone()
return bool(row and row["must_change_password"])
finally:
conn.close()
def load_jwt_secret() -> str:
"""
Load the JWT secret from the database.
Raises RuntimeError if no auth user has been created yet.
"""
conn = get_connection()
try:
cur = conn.execute("SELECT jwt_secret FROM auth_user LIMIT 1")
row = cur.fetchone()
if not row:
raise RuntimeError(
"Auth is not initialized. Wait for the seeded admin bootstrap to complete."
)
return row["jwt_secret"]
finally:
conn.close()
def ensure_default_admin() -> bool:
"""Seed the default admin account on first startup.
Uses a randomly generated diceware passphrase as the bootstrap password.
Returns True when the default admin was created in this call.
"""
bootstrap_pw = generate_bootstrap_password()
try:
create_initial_user(
username = DEFAULT_ADMIN_USERNAME,
password = bootstrap_pw,
jwt_secret = secrets.token_urlsafe(64),
must_change_password = True,
)
return True
except sqlite3.IntegrityError:
return False
def update_password(username: str, new_password: str) -> bool:
"""Update password, clear first-login requirement, rotate JWT secret."""
from .hashing import hash_password
salt, pwd_hash = hash_password(new_password)
jwt_secret = secrets.token_urlsafe(64)
conn = get_connection()
try:
cursor = conn.execute(
"""
UPDATE auth_user
SET password_salt = ?, password_hash = ?, jwt_secret = ?, must_change_password = 0
WHERE username = ?
""",
(salt, pwd_hash, jwt_secret, username),
)
conn.commit()
if cursor.rowcount > 0:
clear_bootstrap_password()
return cursor.rowcount > 0
finally:
conn.close()
def save_refresh_token(token: str, username: str, expires_at: str) -> None:
"""
Store a hashed refresh token with its associated username and expiry.
"""
token_hash = _hash_token(token)
conn = get_connection()
try:
conn.execute(
"""
INSERT INTO refresh_tokens (token_hash, username, expires_at)
VALUES (?, ?, ?)
""",
(token_hash, username, expires_at),
)
conn.commit()
finally:
conn.close()
def verify_refresh_token(token: str) -> Optional[str]:
"""
Verify a refresh token and return the username.
Returns the username if valid and not expired, None otherwise.
The token is NOT consumed — it stays valid until it expires.
"""
token_hash = _hash_token(token)
conn = get_connection()
try:
# Clean up any expired tokens while we're here
conn.execute(
"DELETE FROM refresh_tokens WHERE expires_at < ?",
(datetime.now(timezone.utc).isoformat(),),
)
conn.commit()
cur = conn.execute(
"""
SELECT id, username, expires_at FROM refresh_tokens
WHERE token_hash = ?
""",
(token_hash,),
)
row = cur.fetchone()
if row is None:
return None
# Check expiry
expires_at = datetime.fromisoformat(row["expires_at"])
if datetime.now(timezone.utc) > expires_at:
conn.execute("DELETE FROM refresh_tokens WHERE id = ?", (row["id"],))
conn.commit()
return None
return row["username"]
finally:
conn.close()
def revoke_user_refresh_tokens(username: str) -> None:
"""Revoke all refresh tokens for a user (e.g. on logout)."""
conn = get_connection()
try:
conn.execute("DELETE FROM refresh_tokens WHERE username = ?", (username,))
conn.commit()
finally:
conn.close()
# ---------------------------------------------------------------------------
# API key management
# ---------------------------------------------------------------------------
API_KEY_PREFIX = "sk-unsloth-"
def create_api_key(
username: str,
name: str,
expires_at: Optional[str] = None,
) -> Tuple[str, dict]:
"""Create a new API key for *username*.
Returns ``(raw_key, row_dict)`` where *raw_key* is shown to the user
exactly once. The database only stores the SHA-256 hash.
"""
raw_key = API_KEY_PREFIX + secrets.token_hex(16)
key_hash = _pbkdf2_api_key(raw_key)
key_prefix = raw_key[len(API_KEY_PREFIX) : len(API_KEY_PREFIX) + 8]
now = datetime.now(timezone.utc).isoformat()
conn = get_connection()
try:
conn.execute(
"""
INSERT INTO api_keys (username, key_prefix, key_hash, name, created_at, expires_at)
VALUES (?, ?, ?, ?, ?, ?)
""",
(username, key_prefix, key_hash, name, now, expires_at),
)
conn.commit()
cur = conn.execute("SELECT * FROM api_keys WHERE key_hash = ?", (key_hash,))
row = cur.fetchone()
return raw_key, dict(row)
finally:
conn.close()
def list_api_keys(username: str) -> list:
"""Return all API keys for *username* (never exposes ``key_hash``)."""
conn = get_connection()
try:
cur = conn.execute(
"""
SELECT id, username, key_prefix, name, created_at, last_used_at, expires_at, is_active
FROM api_keys
WHERE username = ?
ORDER BY created_at DESC
""",
(username,),
)
return [dict(row) for row in cur.fetchall()]
finally:
conn.close()
def revoke_api_key(username: str, key_id: int) -> bool:
"""Soft-delete an API key. Returns True if a matching row was found."""
conn = get_connection()
try:
cursor = conn.execute(
"UPDATE api_keys SET is_active = 0 WHERE id = ? AND username = ?",
(key_id, username),
)
conn.commit()
return cursor.rowcount > 0
finally:
conn.close()
def validate_api_key(raw_key: str) -> Optional[str]:
"""Validate *raw_key* and return the owning username, or ``None``.
Also updates ``last_used_at`` on success.
"""
key_hash = _pbkdf2_api_key(raw_key)
conn = get_connection()
try:
cur = conn.execute(
"SELECT id, username, is_active, expires_at FROM api_keys WHERE key_hash = ?",
(key_hash,),
)
row = cur.fetchone()
if row is None:
return None
if not row["is_active"]:
return None
if row["expires_at"] is not None:
expires = datetime.fromisoformat(row["expires_at"])
if datetime.now(timezone.utc) > expires:
return None
conn.execute(
"UPDATE api_keys SET last_used_at = ? WHERE id = ?",
(datetime.now(timezone.utc).isoformat(), row["id"]),
)
conn.commit()
return row["username"]
finally:
conn.close()