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Author SHA1 Message Date
Swifty
50f39e55f7 added ability to disable cors at the backend 2025-09-11 09:59:47 +02:00
440 changed files with 3120 additions and 13435 deletions

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@@ -3,7 +3,6 @@ name: AutoGPT Platform - Deploy Prod Environment
on:
release:
types: [published]
workflow_dispatch:
permissions:
contents: 'read'
@@ -18,8 +17,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
ref: ${{ github.ref_name || 'master' }}
- name: Set up Python
uses: actions/setup-python@v5
@@ -39,7 +36,7 @@ jobs:
DATABASE_URL: ${{ secrets.BACKEND_DATABASE_URL }}
DIRECT_URL: ${{ secrets.BACKEND_DATABASE_URL }}
trigger:
needs: migrate
runs-on: ubuntu-latest
@@ -50,5 +47,4 @@ jobs:
token: ${{ secrets.DEPLOY_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
event-type: build_deploy_prod
client-payload: |
{"ref": "${{ github.ref_name || 'master' }}", "repository": "${{ github.repository }}"}
client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}", "repository": "${{ github.repository }}"}'

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@@ -5,13 +5,6 @@ on:
branches: [ dev ]
paths:
- 'autogpt_platform/**'
workflow_dispatch:
inputs:
git_ref:
description: 'Git ref (branch/tag) of AutoGPT to deploy'
required: true
default: 'master'
type: string
permissions:
contents: 'read'
@@ -26,8 +19,6 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
ref: ${{ github.event.inputs.git_ref || github.ref_name }}
- name: Set up Python
uses: actions/setup-python@v5
@@ -57,4 +48,4 @@ jobs:
token: ${{ secrets.DEPLOY_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
event-type: build_deploy_dev
client-payload: '{"ref": "${{ github.event.inputs.git_ref || github.ref }}", "repository": "${{ github.repository }}"}'
client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}", "repository": "${{ github.repository }}"}'

View File

@@ -37,7 +37,9 @@ jobs:
services:
redis:
image: redis:latest
image: bitnami/redis:6.2
env:
REDIS_PASSWORD: testpassword
ports:
- 6379:6379
rabbitmq:
@@ -202,6 +204,7 @@ jobs:
JWT_VERIFY_KEY: ${{ steps.supabase.outputs.JWT_SECRET }}
REDIS_HOST: "localhost"
REDIS_PORT: "6379"
REDIS_PASSWORD: "testpassword"
ENCRYPTION_KEY: "dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw=" # DO NOT USE IN PRODUCTION!!
env:

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@@ -1,5 +1,3 @@
from typing import Optional
from pydantic import Field
from pydantic_settings import BaseSettings, SettingsConfigDict
@@ -15,8 +13,8 @@ class RateLimitSettings(BaseSettings):
default="6379", description="Redis port", validation_alias="REDIS_PORT"
)
redis_password: Optional[str] = Field(
default=None,
redis_password: str = Field(
default="password",
description="Redis password",
validation_alias="REDIS_PASSWORD",
)

View File

@@ -11,7 +11,7 @@ class RateLimiter:
self,
redis_host: str = RATE_LIMIT_SETTINGS.redis_host,
redis_port: str = RATE_LIMIT_SETTINGS.redis_port,
redis_password: str | None = RATE_LIMIT_SETTINGS.redis_password,
redis_password: str = RATE_LIMIT_SETTINGS.redis_password,
requests_per_minute: int = RATE_LIMIT_SETTINGS.requests_per_minute,
):
self.redis = Redis(

View File

@@ -1,68 +1,90 @@
import asyncio
import inspect
import logging
import threading
import time
from functools import wraps
from typing import (
Any,
Awaitable,
Callable,
ParamSpec,
Protocol,
Tuple,
TypeVar,
cast,
overload,
runtime_checkable,
)
P = ParamSpec("P")
R = TypeVar("R")
R_co = TypeVar("R_co", covariant=True)
logger = logging.getLogger(__name__)
def _make_hashable_key(
args: tuple[Any, ...], kwargs: dict[str, Any]
) -> tuple[Any, ...]:
"""
Convert args and kwargs into a hashable cache key.
@overload
def thread_cached(func: Callable[P, Awaitable[R]]) -> Callable[P, Awaitable[R]]:
pass
Handles unhashable types like dict, list, set by converting them to
their sorted string representations.
"""
def make_hashable(obj: Any) -> Any:
"""Recursively convert an object to a hashable representation."""
if isinstance(obj, dict):
# Sort dict items to ensure consistent ordering
return (
"__dict__",
tuple(sorted((k, make_hashable(v)) for k, v in obj.items())),
)
elif isinstance(obj, (list, tuple)):
return ("__list__", tuple(make_hashable(item) for item in obj))
elif isinstance(obj, set):
return ("__set__", tuple(sorted(make_hashable(item) for item in obj)))
elif hasattr(obj, "__dict__"):
# Handle objects with __dict__ attribute
return ("__obj__", obj.__class__.__name__, make_hashable(obj.__dict__))
else:
# For basic hashable types (str, int, bool, None, etc.)
try:
hash(obj)
return obj
except TypeError:
# Fallback: convert to string representation
return ("__str__", str(obj))
@overload
def thread_cached(func: Callable[P, R]) -> Callable[P, R]:
pass
hashable_args = tuple(make_hashable(arg) for arg in args)
hashable_kwargs = tuple(sorted((k, make_hashable(v)) for k, v in kwargs.items()))
return (hashable_args, hashable_kwargs)
def thread_cached(
func: Callable[P, R] | Callable[P, Awaitable[R]],
) -> Callable[P, R] | Callable[P, Awaitable[R]]:
thread_local = threading.local()
def _clear():
if hasattr(thread_local, "cache"):
del thread_local.cache
if inspect.iscoroutinefunction(func):
async def async_wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
cache = getattr(thread_local, "cache", None)
if cache is None:
cache = thread_local.cache = {}
key = (args, tuple(sorted(kwargs.items())))
if key not in cache:
cache[key] = await cast(Callable[P, Awaitable[R]], func)(
*args, **kwargs
)
return cache[key]
setattr(async_wrapper, "clear_cache", _clear)
return async_wrapper
else:
def sync_wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
cache = getattr(thread_local, "cache", None)
if cache is None:
cache = thread_local.cache = {}
key = (args, tuple(sorted(kwargs.items())))
if key not in cache:
cache[key] = func(*args, **kwargs)
return cache[key]
setattr(sync_wrapper, "clear_cache", _clear)
return sync_wrapper
def clear_thread_cache(func: Callable) -> None:
if clear := getattr(func, "clear_cache", None):
clear()
FuncT = TypeVar("FuncT")
R_co = TypeVar("R_co", covariant=True)
@runtime_checkable
class CachedFunction(Protocol[P, R_co]):
"""Protocol for cached functions with cache management methods."""
class AsyncCachedFunction(Protocol[P, R_co]):
"""Protocol for async functions with cache management methods."""
def cache_clear(self) -> None:
"""Clear all cached entries."""
@@ -72,169 +94,101 @@ class CachedFunction(Protocol[P, R_co]):
"""Get cache statistics."""
return {}
def cache_delete(self, *args: P.args, **kwargs: P.kwargs) -> bool:
"""Delete a specific cache entry by its arguments. Returns True if entry existed."""
return False
def __call__(self, *args: P.args, **kwargs: P.kwargs) -> R_co:
async def __call__(self, *args: P.args, **kwargs: P.kwargs) -> R_co:
"""Call the cached function."""
return None # type: ignore
def cached(
*,
maxsize: int = 128,
ttl_seconds: int | None = None,
) -> Callable[[Callable], CachedFunction]:
def async_ttl_cache(
maxsize: int = 128, ttl_seconds: int | None = None
) -> Callable[[Callable[P, Awaitable[R]]], AsyncCachedFunction[P, R]]:
"""
Thundering herd safe cache decorator for both sync and async functions.
TTL (Time To Live) cache decorator for async functions.
Uses double-checked locking to prevent multiple threads/coroutines from
executing the expensive operation simultaneously during cache misses.
Similar to functools.lru_cache but works with async functions and includes optional TTL.
Args:
func: The function to cache (when used without parentheses)
maxsize: Maximum number of cached entries
ttl_seconds: Time to live in seconds. If None, entries never expire
ttl_seconds: Time to live in seconds. If None, entries never expire (like lru_cache)
Returns:
Decorated function or decorator
Decorator function
Example:
@cache() # Default: maxsize=128, no TTL
def expensive_sync_operation(param: str) -> dict:
# With TTL
@async_ttl_cache(maxsize=1000, ttl_seconds=300)
async def api_call(param: str) -> dict:
return {"result": param}
@cache() # Works with async too
async def expensive_async_operation(param: str) -> dict:
return {"result": param}
@cache(maxsize=1000, ttl_seconds=300) # Custom maxsize and TTL
def another_operation(param: str) -> dict:
# Without TTL (permanent cache like lru_cache)
@async_ttl_cache(maxsize=1000)
async def expensive_computation(param: str) -> dict:
return {"result": param}
"""
def decorator(target_func):
# Cache storage and locks
cache_storage = {}
def decorator(
async_func: Callable[P, Awaitable[R]],
) -> AsyncCachedFunction[P, R]:
# Cache storage - use union type to handle both cases
cache_storage: dict[tuple, R | Tuple[R, float]] = {}
if inspect.iscoroutinefunction(target_func):
# Async function with asyncio.Lock
cache_lock = asyncio.Lock()
@wraps(async_func)
async def wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
# Create cache key from arguments
key = (args, tuple(sorted(kwargs.items())))
current_time = time.time()
@wraps(target_func)
async def async_wrapper(*args: P.args, **kwargs: P.kwargs):
key = _make_hashable_key(args, kwargs)
current_time = time.time()
# Fast path: check cache without lock
if key in cache_storage:
if ttl_seconds is None:
logger.debug(f"Cache hit for {target_func.__name__}")
return cache_storage[key]
else:
cached_data = cache_storage[key]
if isinstance(cached_data, tuple):
result, timestamp = cached_data
if current_time - timestamp < ttl_seconds:
logger.debug(f"Cache hit for {target_func.__name__}")
return result
# Slow path: acquire lock for cache miss/expiry
async with cache_lock:
# Double-check: another coroutine might have populated cache
if key in cache_storage:
if ttl_seconds is None:
return cache_storage[key]
# Check if we have a valid cached entry
if key in cache_storage:
if ttl_seconds is None:
# No TTL - return cached result directly
logger.debug(
f"Cache hit for {async_func.__name__} with key: {str(key)[:50]}"
)
return cast(R, cache_storage[key])
else:
# With TTL - check expiration
cached_data = cache_storage[key]
if isinstance(cached_data, tuple):
result, timestamp = cached_data
if current_time - timestamp < ttl_seconds:
logger.debug(
f"Cache hit for {async_func.__name__} with key: {str(key)[:50]}"
)
return cast(R, result)
else:
cached_data = cache_storage[key]
if isinstance(cached_data, tuple):
result, timestamp = cached_data
if current_time - timestamp < ttl_seconds:
return result
# Expired entry
del cache_storage[key]
logger.debug(
f"Cache entry expired for {async_func.__name__}"
)
# Cache miss - execute function
logger.debug(f"Cache miss for {target_func.__name__}")
result = await target_func(*args, **kwargs)
# Cache miss or expired - fetch fresh data
logger.debug(
f"Cache miss for {async_func.__name__} with key: {str(key)[:50]}"
)
result = await async_func(*args, **kwargs)
# Store result
if ttl_seconds is None:
cache_storage[key] = result
else:
cache_storage[key] = (result, current_time)
# Store in cache
if ttl_seconds is None:
cache_storage[key] = result
else:
cache_storage[key] = (result, current_time)
# Cleanup if needed
if len(cache_storage) > maxsize:
cutoff = maxsize // 2
oldest_keys = (
list(cache_storage.keys())[:-cutoff] if cutoff > 0 else []
)
for old_key in oldest_keys:
cache_storage.pop(old_key, None)
# Simple cleanup when cache gets too large
if len(cache_storage) > maxsize:
# Remove oldest entries (simple FIFO cleanup)
cutoff = maxsize // 2
oldest_keys = list(cache_storage.keys())[:-cutoff] if cutoff > 0 else []
for old_key in oldest_keys:
cache_storage.pop(old_key, None)
logger.debug(
f"Cache cleanup: removed {len(oldest_keys)} entries for {async_func.__name__}"
)
return result
return result
wrapper = async_wrapper
else:
# Sync function with threading.Lock
cache_lock = threading.Lock()
@wraps(target_func)
def sync_wrapper(*args: P.args, **kwargs: P.kwargs):
key = _make_hashable_key(args, kwargs)
current_time = time.time()
# Fast path: check cache without lock
if key in cache_storage:
if ttl_seconds is None:
logger.debug(f"Cache hit for {target_func.__name__}")
return cache_storage[key]
else:
cached_data = cache_storage[key]
if isinstance(cached_data, tuple):
result, timestamp = cached_data
if current_time - timestamp < ttl_seconds:
logger.debug(f"Cache hit for {target_func.__name__}")
return result
# Slow path: acquire lock for cache miss/expiry
with cache_lock:
# Double-check: another thread might have populated cache
if key in cache_storage:
if ttl_seconds is None:
return cache_storage[key]
else:
cached_data = cache_storage[key]
if isinstance(cached_data, tuple):
result, timestamp = cached_data
if current_time - timestamp < ttl_seconds:
return result
# Cache miss - execute function
logger.debug(f"Cache miss for {target_func.__name__}")
result = target_func(*args, **kwargs)
# Store result
if ttl_seconds is None:
cache_storage[key] = result
else:
cache_storage[key] = (result, current_time)
# Cleanup if needed
if len(cache_storage) > maxsize:
cutoff = maxsize // 2
oldest_keys = (
list(cache_storage.keys())[:-cutoff] if cutoff > 0 else []
)
for old_key in oldest_keys:
cache_storage.pop(old_key, None)
return result
wrapper = sync_wrapper
# Add cache management methods
# Add cache management methods (similar to functools.lru_cache)
def cache_clear() -> None:
cache_storage.clear()
@@ -245,84 +199,68 @@ def cached(
"ttl_seconds": ttl_seconds,
}
def cache_delete(*args, **kwargs) -> bool:
"""Delete a specific cache entry. Returns True if entry existed."""
key = _make_hashable_key(args, kwargs)
if key in cache_storage:
del cache_storage[key]
return True
return False
# Attach methods to wrapper
setattr(wrapper, "cache_clear", cache_clear)
setattr(wrapper, "cache_info", cache_info)
setattr(wrapper, "cache_delete", cache_delete)
return cast(CachedFunction, wrapper)
return cast(AsyncCachedFunction[P, R], wrapper)
return decorator
def thread_cached(func):
"""
Thread-local cache decorator for both sync and async functions.
@overload
def async_cache(
func: Callable[P, Awaitable[R]],
) -> AsyncCachedFunction[P, R]:
pass
Each thread gets its own cache, which is useful for request-scoped caching
in web applications where you want to cache within a single request but
not across requests.
@overload
def async_cache(
func: None = None,
*,
maxsize: int = 128,
) -> Callable[[Callable[P, Awaitable[R]]], AsyncCachedFunction[P, R]]:
pass
def async_cache(
func: Callable[P, Awaitable[R]] | None = None,
*,
maxsize: int = 128,
) -> (
AsyncCachedFunction[P, R]
| Callable[[Callable[P, Awaitable[R]]], AsyncCachedFunction[P, R]]
):
"""
Process-level cache decorator for async functions (no TTL).
Similar to functools.lru_cache but works with async functions.
This is a convenience wrapper around async_ttl_cache with ttl_seconds=None.
Args:
func: The function to cache
func: The async function to cache (when used without parentheses)
maxsize: Maximum number of cached entries
Returns:
Decorated function with thread-local caching
Decorated function or decorator
Example:
@thread_cached
def expensive_operation(param: str) -> dict:
# Without parentheses (uses default maxsize=128)
@async_cache
async def get_data(param: str) -> dict:
return {"result": param}
@thread_cached # Works with async too
async def expensive_async_operation(param: str) -> dict:
# With parentheses and custom maxsize
@async_cache(maxsize=1000)
async def expensive_computation(param: str) -> dict:
# Expensive computation here
return {"result": param}
"""
thread_local = threading.local()
def _clear():
if hasattr(thread_local, "cache"):
del thread_local.cache
if inspect.iscoroutinefunction(func):
@wraps(func)
async def async_wrapper(*args, **kwargs):
cache = getattr(thread_local, "cache", None)
if cache is None:
cache = thread_local.cache = {}
key = _make_hashable_key(args, kwargs)
if key not in cache:
cache[key] = await func(*args, **kwargs)
return cache[key]
setattr(async_wrapper, "clear_cache", _clear)
return async_wrapper
if func is None:
# Called with parentheses @async_cache() or @async_cache(maxsize=...)
return async_ttl_cache(maxsize=maxsize, ttl_seconds=None)
else:
@wraps(func)
def sync_wrapper(*args, **kwargs):
cache = getattr(thread_local, "cache", None)
if cache is None:
cache = thread_local.cache = {}
key = _make_hashable_key(args, kwargs)
if key not in cache:
cache[key] = func(*args, **kwargs)
return cache[key]
setattr(sync_wrapper, "clear_cache", _clear)
return sync_wrapper
def clear_thread_cache(func: Callable) -> None:
"""Clear thread-local cache for a function."""
if clear := getattr(func, "clear_cache", None):
clear()
# Called without parentheses @async_cache
decorator = async_ttl_cache(maxsize=maxsize, ttl_seconds=None)
return decorator(func)

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@@ -16,7 +16,12 @@ from unittest.mock import Mock
import pytest
from autogpt_libs.utils.cache import cached, clear_thread_cache, thread_cached
from autogpt_libs.utils.cache import (
async_cache,
async_ttl_cache,
clear_thread_cache,
thread_cached,
)
class TestThreadCached:
@@ -325,202 +330,102 @@ class TestThreadCached:
assert mock.call_count == 2
class TestCache:
"""Tests for the unified @cache decorator (works for both sync and async)."""
def test_basic_sync_caching(self):
"""Test basic sync caching functionality."""
call_count = 0
@cached()
def expensive_sync_function(x: int, y: int = 0) -> int:
nonlocal call_count
call_count += 1
return x + y
# First call
result1 = expensive_sync_function(1, 2)
assert result1 == 3
assert call_count == 1
# Second call with same args - should use cache
result2 = expensive_sync_function(1, 2)
assert result2 == 3
assert call_count == 1
# Different args - should call function again
result3 = expensive_sync_function(2, 3)
assert result3 == 5
assert call_count == 2
class TestAsyncTTLCache:
"""Tests for the @async_ttl_cache decorator."""
@pytest.mark.asyncio
async def test_basic_async_caching(self):
"""Test basic async caching functionality."""
async def test_basic_caching(self):
"""Test basic caching functionality."""
call_count = 0
@cached()
async def expensive_async_function(x: int, y: int = 0) -> int:
@async_ttl_cache(maxsize=10, ttl_seconds=60)
async def cached_function(x: int, y: int = 0) -> int:
nonlocal call_count
call_count += 1
await asyncio.sleep(0.01) # Simulate async work
return x + y
# First call
result1 = await expensive_async_function(1, 2)
result1 = await cached_function(1, 2)
assert result1 == 3
assert call_count == 1
# Second call with same args - should use cache
result2 = await expensive_async_function(1, 2)
result2 = await cached_function(1, 2)
assert result2 == 3
assert call_count == 1
assert call_count == 1 # No additional call
# Different args - should call function again
result3 = await expensive_async_function(2, 3)
result3 = await cached_function(2, 3)
assert result3 == 5
assert call_count == 2
def test_sync_thundering_herd_protection(self):
"""Test that concurrent sync calls don't cause thundering herd."""
call_count = 0
results = []
@cached()
def slow_function(x: int) -> int:
nonlocal call_count
call_count += 1
time.sleep(0.1) # Simulate expensive operation
return x * x
def worker():
result = slow_function(5)
results.append(result)
# Launch multiple concurrent threads
with ThreadPoolExecutor(max_workers=5) as executor:
futures = [executor.submit(worker) for _ in range(5)]
for future in futures:
future.result()
# All results should be the same
assert all(result == 25 for result in results)
# Only one thread should have executed the expensive operation
assert call_count == 1
@pytest.mark.asyncio
async def test_async_thundering_herd_protection(self):
"""Test that concurrent async calls don't cause thundering herd."""
async def test_ttl_expiration(self):
"""Test that cache entries expire after TTL."""
call_count = 0
@cached()
async def slow_async_function(x: int) -> int:
@async_ttl_cache(maxsize=10, ttl_seconds=1) # Short TTL
async def short_lived_cache(x: int) -> int:
nonlocal call_count
call_count += 1
await asyncio.sleep(0.1) # Simulate expensive operation
return x * x
# Launch concurrent coroutines
tasks = [slow_async_function(7) for _ in range(5)]
results = await asyncio.gather(*tasks)
# All results should be the same
assert all(result == 49 for result in results)
# Only one coroutine should have executed the expensive operation
assert call_count == 1
def test_ttl_functionality(self):
"""Test TTL functionality with sync function."""
call_count = 0
@cached(maxsize=10, ttl_seconds=1) # Short TTL
def ttl_function(x: int) -> int:
nonlocal call_count
call_count += 1
return x * 3
return x * 2
# First call
result1 = ttl_function(3)
assert result1 == 9
result1 = await short_lived_cache(5)
assert result1 == 10
assert call_count == 1
# Second call immediately - should use cache
result2 = ttl_function(3)
assert result2 == 9
assert call_count == 1
# Wait for TTL to expire
time.sleep(1.1)
# Third call after expiration - should call function again
result3 = ttl_function(3)
assert result3 == 9
assert call_count == 2
@pytest.mark.asyncio
async def test_async_ttl_functionality(self):
"""Test TTL functionality with async function."""
call_count = 0
@cached(maxsize=10, ttl_seconds=1) # Short TTL
async def async_ttl_function(x: int) -> int:
nonlocal call_count
call_count += 1
await asyncio.sleep(0.01)
return x * 4
# First call
result1 = await async_ttl_function(3)
assert result1 == 12
assert call_count == 1
# Second call immediately - should use cache
result2 = await async_ttl_function(3)
assert result2 == 12
result2 = await short_lived_cache(5)
assert result2 == 10
assert call_count == 1
# Wait for TTL to expire
await asyncio.sleep(1.1)
# Third call after expiration - should call function again
result3 = await async_ttl_function(3)
assert result3 == 12
result3 = await short_lived_cache(5)
assert result3 == 10
assert call_count == 2
def test_cache_info(self):
@pytest.mark.asyncio
async def test_cache_info(self):
"""Test cache info functionality."""
@cached(maxsize=10, ttl_seconds=60)
def info_test_function(x: int) -> int:
@async_ttl_cache(maxsize=5, ttl_seconds=300)
async def info_test_function(x: int) -> int:
return x * 3
# Check initial cache info
info = info_test_function.cache_info()
assert info["size"] == 0
assert info["maxsize"] == 10
assert info["ttl_seconds"] == 60
assert info["maxsize"] == 5
assert info["ttl_seconds"] == 300
# Add an entry
info_test_function(1)
await info_test_function(1)
info = info_test_function.cache_info()
assert info["size"] == 1
def test_cache_clear(self):
@pytest.mark.asyncio
async def test_cache_clear(self):
"""Test cache clearing functionality."""
call_count = 0
@cached()
def clearable_function(x: int) -> int:
@async_ttl_cache(maxsize=10, ttl_seconds=60)
async def clearable_function(x: int) -> int:
nonlocal call_count
call_count += 1
return x * 4
# First call
result1 = clearable_function(2)
result1 = await clearable_function(2)
assert result1 == 8
assert call_count == 1
# Second call - should use cache
result2 = clearable_function(2)
result2 = await clearable_function(2)
assert result2 == 8
assert call_count == 1
@@ -528,149 +433,273 @@ class TestCache:
clearable_function.cache_clear()
# Third call after clear - should call function again
result3 = clearable_function(2)
result3 = await clearable_function(2)
assert result3 == 8
assert call_count == 2
@pytest.mark.asyncio
async def test_async_cache_clear(self):
"""Test cache clearing functionality with async function."""
async def test_maxsize_cleanup(self):
"""Test that cache cleans up when maxsize is exceeded."""
call_count = 0
@cached()
async def async_clearable_function(x: int) -> int:
@async_ttl_cache(maxsize=3, ttl_seconds=60)
async def size_limited_function(x: int) -> int:
nonlocal call_count
call_count += 1
await asyncio.sleep(0.01)
return x * 5
return x**2
# First call
result1 = await async_clearable_function(2)
# Fill cache to maxsize
await size_limited_function(1) # call_count: 1
await size_limited_function(2) # call_count: 2
await size_limited_function(3) # call_count: 3
info = size_limited_function.cache_info()
assert info["size"] == 3
# Add one more entry - should trigger cleanup
await size_limited_function(4) # call_count: 4
# Cache size should be reduced (cleanup removes oldest entries)
info = size_limited_function.cache_info()
assert info["size"] is not None and info["size"] <= 3 # Should be cleaned up
@pytest.mark.asyncio
async def test_argument_variations(self):
"""Test caching with different argument patterns."""
call_count = 0
@async_ttl_cache(maxsize=10, ttl_seconds=60)
async def arg_test_function(a: int, b: str = "default", *, c: int = 100) -> str:
nonlocal call_count
call_count += 1
return f"{a}-{b}-{c}"
# Different ways to call with same logical arguments
result1 = await arg_test_function(1, "test", c=200)
assert call_count == 1
# Same arguments, same order - should use cache
result2 = await arg_test_function(1, "test", c=200)
assert call_count == 1
assert result1 == result2
# Different arguments - should call function
result3 = await arg_test_function(2, "test", c=200)
assert call_count == 2
assert result1 != result3
@pytest.mark.asyncio
async def test_exception_handling(self):
"""Test that exceptions are not cached."""
call_count = 0
@async_ttl_cache(maxsize=10, ttl_seconds=60)
async def exception_function(x: int) -> int:
nonlocal call_count
call_count += 1
if x < 0:
raise ValueError("Negative value not allowed")
return x * 2
# Successful call - should be cached
result1 = await exception_function(5)
assert result1 == 10
assert call_count == 1
# Second call - should use cache
result2 = await async_clearable_function(2)
# Same successful call - should use cache
result2 = await exception_function(5)
assert result2 == 10
assert call_count == 1
# Clear cache
async_clearable_function.cache_clear()
# Third call after clear - should call function again
result3 = await async_clearable_function(2)
assert result3 == 10
# Exception call - should not be cached
with pytest.raises(ValueError):
await exception_function(-1)
assert call_count == 2
# Same exception call - should call again (not cached)
with pytest.raises(ValueError):
await exception_function(-1)
assert call_count == 3
@pytest.mark.asyncio
async def test_async_function_returns_results_not_coroutines(self):
"""Test that cached async functions return actual results, not coroutines."""
async def test_concurrent_calls(self):
"""Test caching behavior with concurrent calls."""
call_count = 0
@cached()
async def async_result_function(x: int) -> str:
@async_ttl_cache(maxsize=10, ttl_seconds=60)
async def concurrent_function(x: int) -> int:
nonlocal call_count
call_count += 1
await asyncio.sleep(0.01)
return f"result_{x}"
await asyncio.sleep(0.05) # Simulate work
return x * x
# Launch concurrent calls with same arguments
tasks = [concurrent_function(3) for _ in range(5)]
results = await asyncio.gather(*tasks)
# All results should be the same
assert all(result == 9 for result in results)
# Note: Due to race conditions, call_count might be up to 5 for concurrent calls
# This tests that the cache doesn't break under concurrent access
assert 1 <= call_count <= 5
class TestAsyncCache:
"""Tests for the @async_cache decorator (no TTL)."""
@pytest.mark.asyncio
async def test_basic_caching_no_ttl(self):
"""Test basic caching functionality without TTL."""
call_count = 0
@async_cache(maxsize=10)
async def cached_function(x: int, y: int = 0) -> int:
nonlocal call_count
call_count += 1
await asyncio.sleep(0.01) # Simulate async work
return x + y
# First call
result1 = await async_result_function(1)
assert result1 == "result_1"
assert isinstance(result1, str) # Should be string, not coroutine
result1 = await cached_function(1, 2)
assert result1 == 3
assert call_count == 1
# Second call - should return cached result (string), not coroutine
result2 = await async_result_function(1)
assert result2 == "result_1"
assert isinstance(result2, str) # Should be string, not coroutine
assert call_count == 1 # Function should not be called again
# Second call with same args - should use cache
result2 = await cached_function(1, 2)
assert result2 == 3
assert call_count == 1 # No additional call
# Verify results are identical
assert result1 is result2 # Should be same cached object
# Third call after some time - should still use cache (no TTL)
await asyncio.sleep(0.05)
result3 = await cached_function(1, 2)
assert result3 == 3
assert call_count == 1 # Still no additional call
def test_cache_delete(self):
"""Test selective cache deletion functionality."""
call_count = 0
@cached()
def deletable_function(x: int) -> int:
nonlocal call_count
call_count += 1
return x * 6
# First call for x=1
result1 = deletable_function(1)
assert result1 == 6
assert call_count == 1
# First call for x=2
result2 = deletable_function(2)
assert result2 == 12
# Different args - should call function again
result4 = await cached_function(2, 3)
assert result4 == 5
assert call_count == 2
# Second calls - should use cache
assert deletable_function(1) == 6
assert deletable_function(2) == 12
assert call_count == 2
# Delete specific entry for x=1
was_deleted = deletable_function.cache_delete(1)
assert was_deleted is True
# Call with x=1 should execute function again
result3 = deletable_function(1)
assert result3 == 6
assert call_count == 3
# Call with x=2 should still use cache
assert deletable_function(2) == 12
assert call_count == 3
# Try to delete non-existent entry
was_deleted = deletable_function.cache_delete(99)
assert was_deleted is False
@pytest.mark.asyncio
async def test_async_cache_delete(self):
"""Test selective cache deletion functionality with async function."""
async def test_no_ttl_vs_ttl_behavior(self):
"""Test the difference between TTL and no-TTL caching."""
ttl_call_count = 0
no_ttl_call_count = 0
@async_ttl_cache(maxsize=10, ttl_seconds=1) # Short TTL
async def ttl_function(x: int) -> int:
nonlocal ttl_call_count
ttl_call_count += 1
return x * 2
@async_cache(maxsize=10) # No TTL
async def no_ttl_function(x: int) -> int:
nonlocal no_ttl_call_count
no_ttl_call_count += 1
return x * 2
# First calls
await ttl_function(5)
await no_ttl_function(5)
assert ttl_call_count == 1
assert no_ttl_call_count == 1
# Wait for TTL to expire
await asyncio.sleep(1.1)
# Second calls after TTL expiry
await ttl_function(5) # Should call function again (TTL expired)
await no_ttl_function(5) # Should use cache (no TTL)
assert ttl_call_count == 2 # TTL function called again
assert no_ttl_call_count == 1 # No-TTL function still cached
@pytest.mark.asyncio
async def test_async_cache_info(self):
"""Test cache info for no-TTL cache."""
@async_cache(maxsize=5)
async def info_test_function(x: int) -> int:
return x * 3
# Check initial cache info
info = info_test_function.cache_info()
assert info["size"] == 0
assert info["maxsize"] == 5
assert info["ttl_seconds"] is None # No TTL
# Add an entry
await info_test_function(1)
info = info_test_function.cache_info()
assert info["size"] == 1
class TestTTLOptional:
"""Tests for optional TTL functionality."""
@pytest.mark.asyncio
async def test_ttl_none_behavior(self):
"""Test that ttl_seconds=None works like no TTL."""
call_count = 0
@cached()
async def async_deletable_function(x: int) -> int:
@async_ttl_cache(maxsize=10, ttl_seconds=None)
async def no_ttl_via_none(x: int) -> int:
nonlocal call_count
call_count += 1
await asyncio.sleep(0.01)
return x * 7
return x**2
# First call for x=1
result1 = await async_deletable_function(1)
assert result1 == 7
# First call
result1 = await no_ttl_via_none(3)
assert result1 == 9
assert call_count == 1
# First call for x=2
result2 = await async_deletable_function(2)
assert result2 == 14
assert call_count == 2
# Wait (would expire if there was TTL)
await asyncio.sleep(0.1)
# Second calls - should use cache
assert await async_deletable_function(1) == 7
assert await async_deletable_function(2) == 14
assert call_count == 2
# Second call - should still use cache
result2 = await no_ttl_via_none(3)
assert result2 == 9
assert call_count == 1 # No additional call
# Delete specific entry for x=1
was_deleted = async_deletable_function.cache_delete(1)
assert was_deleted is True
# Check cache info
info = no_ttl_via_none.cache_info()
assert info["ttl_seconds"] is None
# Call with x=1 should execute function again
result3 = await async_deletable_function(1)
assert result3 == 7
assert call_count == 3
@pytest.mark.asyncio
async def test_cache_options_comparison(self):
"""Test different cache options work as expected."""
ttl_calls = 0
no_ttl_calls = 0
# Call with x=2 should still use cache
assert await async_deletable_function(2) == 14
assert call_count == 3
@async_ttl_cache(maxsize=10, ttl_seconds=1) # With TTL
async def ttl_function(x: int) -> int:
nonlocal ttl_calls
ttl_calls += 1
return x * 10
# Try to delete non-existent entry
was_deleted = async_deletable_function.cache_delete(99)
assert was_deleted is False
@async_cache(maxsize=10) # Process-level cache (no TTL)
async def process_function(x: int) -> int:
nonlocal no_ttl_calls
no_ttl_calls += 1
return x * 10
# Both should cache initially
await ttl_function(3)
await process_function(3)
assert ttl_calls == 1
assert no_ttl_calls == 1
# Immediate second calls - both should use cache
await ttl_function(3)
await process_function(3)
assert ttl_calls == 1
assert no_ttl_calls == 1
# Wait for TTL to expire
await asyncio.sleep(1.1)
# After TTL expiry
await ttl_function(3) # Should call function again
await process_function(3) # Should still use cache
assert ttl_calls == 2 # TTL cache expired, called again
assert no_ttl_calls == 1 # Process cache never expires

View File

@@ -21,7 +21,7 @@ PRISMA_SCHEMA="postgres/schema.prisma"
# Redis Configuration
REDIS_HOST=localhost
REDIS_PORT=6379
# REDIS_PASSWORD=
REDIS_PASSWORD=password
# RabbitMQ Credentials
RABBITMQ_DEFAULT_USER=rabbitmq_user_default
@@ -66,11 +66,6 @@ NVIDIA_API_KEY=
GITHUB_CLIENT_ID=
GITHUB_CLIENT_SECRET=
# Notion OAuth App server credentials - https://developers.notion.com/docs/authorization
# Configure a public integration
NOTION_CLIENT_ID=
NOTION_CLIENT_SECRET=
# Google OAuth App server credentials - https://console.cloud.google.com/apis/credentials, and enable gmail api and set scopes
# https://console.cloud.google.com/apis/credentials/consent ?project=<your_project_id>
# You'll need to add/enable the following scopes (minimum):

View File

@@ -9,12 +9,4 @@ secrets/*
!secrets/.gitkeep
*.ignore.*
*.ign.*
# Load test results and reports
load-tests/*_RESULTS.md
load-tests/*_REPORT.md
load-tests/results/
load-tests/*.json
load-tests/*.log
load-tests/node_modules/*
*.ign.*

View File

@@ -9,15 +9,8 @@ WORKDIR /app
RUN echo 'Acquire::http::Pipeline-Depth 0;\nAcquire::http::No-Cache true;\nAcquire::BrokenProxy true;\n' > /etc/apt/apt.conf.d/99fixbadproxy
# Install Node.js repository key and setup
# Update package list and install Python and build dependencies
RUN apt-get update --allow-releaseinfo-change --fix-missing \
&& apt-get install -y curl ca-certificates gnupg \
&& mkdir -p /etc/apt/keyrings \
&& curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg \
&& echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_20.x nodistro main" | tee /etc/apt/sources.list.d/nodesource.list
# Update package list and install Python, Node.js, and build dependencies
RUN apt-get update \
&& apt-get install -y \
python3.13 \
python3.13-dev \
@@ -27,9 +20,7 @@ RUN apt-get update \
libpq5 \
libz-dev \
libssl-dev \
postgresql-client \
nodejs \
&& rm -rf /var/lib/apt/lists/*
postgresql-client
ENV POETRY_HOME=/opt/poetry
ENV POETRY_NO_INTERACTION=1
@@ -63,18 +54,13 @@ ENV PATH=/opt/poetry/bin:$PATH
# Install Python without upgrading system-managed packages
RUN apt-get update && apt-get install -y \
python3.13 \
python3-pip \
&& rm -rf /var/lib/apt/lists/*
python3-pip
# Copy only necessary files from builder
COPY --from=builder /app /app
COPY --from=builder /usr/local/lib/python3* /usr/local/lib/python3*
COPY --from=builder /usr/local/bin/poetry /usr/local/bin/poetry
# Copy Node.js installation for Prisma
COPY --from=builder /usr/bin/node /usr/bin/node
COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules
COPY --from=builder /usr/bin/npm /usr/bin/npm
COPY --from=builder /usr/bin/npx /usr/bin/npx
# Copy Prisma binaries
COPY --from=builder /root/.cache/prisma-python/binaries /root/.cache/prisma-python/binaries
ENV PATH="/app/autogpt_platform/backend/.venv/bin:$PATH"

View File

@@ -1,3 +1,4 @@
import functools
import importlib
import logging
import os
@@ -5,8 +6,6 @@ import re
from pathlib import Path
from typing import TYPE_CHECKING, TypeVar
from autogpt_libs.utils.cache import cached
logger = logging.getLogger(__name__)
@@ -16,7 +15,7 @@ if TYPE_CHECKING:
T = TypeVar("T")
@cached()
@functools.cache
def load_all_blocks() -> dict[str, type["Block"]]:
from backend.data.block import Block
from backend.util.settings import Config

View File

@@ -241,7 +241,6 @@ class AirtableCreateRecordsBlock(Block):
class Output(BlockSchema):
records: list[dict] = SchemaField(description="Array of created record objects")
details: dict = SchemaField(description="Details of the created records")
def __init__(self):
super().__init__(
@@ -280,9 +279,6 @@ class AirtableCreateRecordsBlock(Block):
result_records = normalized_data["records"]
yield "records", result_records
details = data.get("details", None)
if details:
yield "details", details
class AirtableUpdateRecordsBlock(Block):

View File

@@ -113,7 +113,6 @@ class DataForSeoClient:
include_serp_info: bool = False,
include_clickstream_data: bool = False,
limit: int = 100,
depth: Optional[int] = None,
) -> List[Dict[str, Any]]:
"""
Get related keywords from DataForSEO Labs.
@@ -126,7 +125,6 @@ class DataForSeoClient:
include_serp_info: Include SERP data
include_clickstream_data: Include clickstream metrics
limit: Maximum number of results (up to 3000)
depth: Keyword search depth (0-4), controls number of returned keywords
Returns:
API response with related keywords
@@ -150,8 +148,6 @@ class DataForSeoClient:
task_data["include_clickstream_data"] = include_clickstream_data
if limit is not None:
task_data["limit"] = limit
if depth is not None:
task_data["depth"] = depth
payload = [task_data]

View File

@@ -78,12 +78,6 @@ class DataForSeoRelatedKeywordsBlock(Block):
ge=1,
le=3000,
)
depth: int = SchemaField(
description="Keyword search depth (0-4). Controls the number of returned keywords: 0=1 keyword, 1=~8 keywords, 2=~72 keywords, 3=~584 keywords, 4=~4680 keywords",
default=1,
ge=0,
le=4,
)
class Output(BlockSchema):
related_keywords: List[RelatedKeyword] = SchemaField(
@@ -160,7 +154,6 @@ class DataForSeoRelatedKeywordsBlock(Block):
include_serp_info=input_data.include_serp_info,
include_clickstream_data=input_data.include_clickstream_data,
limit=input_data.limit,
depth=input_data.depth,
)
async def run(

View File

@@ -10,6 +10,7 @@ from backend.util.settings import Config
from backend.util.text import TextFormatter
from backend.util.type import LongTextType, MediaFileType, ShortTextType
formatter = TextFormatter()
config = Config()
@@ -131,11 +132,6 @@ class AgentOutputBlock(Block):
default="",
advanced=True,
)
escape_html: bool = SchemaField(
default=False,
advanced=True,
description="Whether to escape special characters in the inserted values to be HTML-safe. Enable for HTML output, disable for plain text.",
)
advanced: bool = SchemaField(
description="Whether to treat the output as advanced.",
default=False,
@@ -197,7 +193,6 @@ class AgentOutputBlock(Block):
"""
if input_data.format:
try:
formatter = TextFormatter(autoescape=input_data.escape_html)
yield "output", formatter.format_string(
input_data.format, {input_data.name: input_data.value}
)

View File

@@ -1,9 +1,5 @@
# This file contains a lot of prompt block strings that would trigger "line too long"
# flake8: noqa: E501
import ast
import logging
import re
import secrets
from abc import ABC
from enum import Enum, EnumMeta
from json import JSONDecodeError
@@ -31,7 +27,7 @@ from backend.util.prompt import compress_prompt, estimate_token_count
from backend.util.text import TextFormatter
logger = TruncatedLogger(logging.getLogger(__name__), "[LLM-Block]")
fmt = TextFormatter(autoescape=False)
fmt = TextFormatter()
LLMProviderName = Literal[
ProviderName.AIML_API,
@@ -208,13 +204,13 @@ MODEL_METADATA = {
"anthropic", 200000, 32000
), # claude-opus-4-1-20250805
LlmModel.CLAUDE_4_OPUS: ModelMetadata(
"anthropic", 200000, 32000
"anthropic", 200000, 8192
), # claude-4-opus-20250514
LlmModel.CLAUDE_4_SONNET: ModelMetadata(
"anthropic", 200000, 64000
"anthropic", 200000, 8192
), # claude-4-sonnet-20250514
LlmModel.CLAUDE_3_7_SONNET: ModelMetadata(
"anthropic", 200000, 64000
"anthropic", 200000, 8192
), # claude-3-7-sonnet-20250219
LlmModel.CLAUDE_3_5_SONNET: ModelMetadata(
"anthropic", 200000, 8192
@@ -386,9 +382,7 @@ def extract_openai_tool_calls(response) -> list[ToolContentBlock] | None:
return None
def get_parallel_tool_calls_param(
llm_model: LlmModel, parallel_tool_calls: bool | None
):
def get_parallel_tool_calls_param(llm_model: LlmModel, parallel_tool_calls):
"""Get the appropriate parallel_tool_calls parameter for OpenAI-compatible APIs."""
if llm_model.startswith("o") or parallel_tool_calls is None:
return openai.NOT_GIVEN
@@ -399,8 +393,8 @@ async def llm_call(
credentials: APIKeyCredentials,
llm_model: LlmModel,
prompt: list[dict],
json_format: bool,
max_tokens: int | None,
force_json_output: bool = False,
tools: list[dict] | None = None,
ollama_host: str = "localhost:11434",
parallel_tool_calls=None,
@@ -413,7 +407,7 @@ async def llm_call(
credentials: The API key credentials to use.
llm_model: The LLM model to use.
prompt: The prompt to send to the LLM.
force_json_output: Whether the response should be in JSON format.
json_format: Whether the response should be in JSON format.
max_tokens: The maximum number of tokens to generate in the chat completion.
tools: The tools to use in the chat completion.
ollama_host: The host for ollama to use.
@@ -452,7 +446,7 @@ async def llm_call(
llm_model, parallel_tool_calls
)
if force_json_output:
if json_format:
response_format = {"type": "json_object"}
response = await oai_client.chat.completions.create(
@@ -565,7 +559,7 @@ async def llm_call(
raise ValueError("Groq does not support tools.")
client = AsyncGroq(api_key=credentials.api_key.get_secret_value())
response_format = {"type": "json_object"} if force_json_output else None
response_format = {"type": "json_object"} if json_format else None
response = await client.chat.completions.create(
model=llm_model.value,
messages=prompt, # type: ignore
@@ -723,7 +717,7 @@ async def llm_call(
)
response_format = None
if force_json_output:
if json_format:
response_format = {"type": "json_object"}
parallel_tool_calls_param = get_parallel_tool_calls_param(
@@ -786,17 +780,6 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
description="The language model to use for answering the prompt.",
advanced=False,
)
force_json_output: bool = SchemaField(
title="Restrict LLM to pure JSON output",
default=False,
description=(
"Whether to force the LLM to produce a JSON-only response. "
"This can increase the block's reliability, "
"but may also reduce the quality of the response "
"because it prohibits the LLM from reasoning "
"before providing its JSON response."
),
)
credentials: AICredentials = AICredentialsField()
sys_prompt: str = SchemaField(
title="System Prompt",
@@ -865,18 +848,17 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
"llm_call": lambda *args, **kwargs: LLMResponse(
raw_response="",
prompt=[""],
response=(
'<json_output id="test123456">{\n'
' "key1": "key1Value",\n'
' "key2": "key2Value"\n'
"}</json_output>"
response=json.dumps(
{
"key1": "key1Value",
"key2": "key2Value",
}
),
tool_calls=None,
prompt_tokens=0,
completion_tokens=0,
reasoning=None,
),
"get_collision_proof_output_tag_id": lambda *args: "test123456",
)
},
)
@@ -885,9 +867,9 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
credentials: APIKeyCredentials,
llm_model: LlmModel,
prompt: list[dict],
json_format: bool,
compress_prompt_to_fit: bool,
max_tokens: int | None,
force_json_output: bool = False,
compress_prompt_to_fit: bool = True,
tools: list[dict] | None = None,
ollama_host: str = "localhost:11434",
) -> LLMResponse:
@@ -900,8 +882,8 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
credentials=credentials,
llm_model=llm_model,
prompt=prompt,
json_format=json_format,
max_tokens=max_tokens,
force_json_output=force_json_output,
tools=tools,
ollama_host=ollama_host,
compress_prompt_to_fit=compress_prompt_to_fit,
@@ -913,6 +895,10 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
logger.debug(f"Calling LLM with input data: {input_data}")
prompt = [json.to_dict(p) for p in input_data.conversation_history]
def trim_prompt(s: str) -> str:
lines = s.strip().split("\n")
return "\n".join([line.strip().lstrip("|") for line in lines])
values = input_data.prompt_values
if values:
input_data.prompt = fmt.format_string(input_data.prompt, values)
@@ -921,15 +907,27 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
if input_data.sys_prompt:
prompt.append({"role": "system", "content": input_data.sys_prompt})
# Use a one-time unique tag to prevent collisions with user/LLM content
output_tag_id = self.get_collision_proof_output_tag_id()
output_tag_start = f'<json_output id="{output_tag_id}">'
if input_data.expected_format:
sys_prompt = self.response_format_instructions(
input_data.expected_format,
list_mode=input_data.list_result,
pure_json_mode=input_data.force_json_output,
output_tag_start=output_tag_start,
expected_format = [
f'"{k}": "{v}"' for k, v in input_data.expected_format.items()
]
if input_data.list_result:
format_prompt = (
f'"results": [\n {{\n {", ".join(expected_format)}\n }}\n]'
)
else:
format_prompt = "\n ".join(expected_format)
sys_prompt = trim_prompt(
f"""
|Reply strictly only in the following JSON format:
|{{
| {format_prompt}
|}}
|
|Ensure the response is valid JSON. Do not include any additional text outside of the JSON.
|If you cannot provide all the keys, provide an empty string for the values you cannot answer.
"""
)
prompt.append({"role": "system", "content": sys_prompt})
@@ -947,21 +945,18 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
except JSONDecodeError as e:
return f"JSON decode error: {e}"
error_feedback_message = ""
logger.debug(f"LLM request: {prompt}")
retry_prompt = ""
llm_model = input_data.model
for retry_count in range(input_data.retry):
logger.debug(f"LLM request: {prompt}")
try:
llm_response = await self.llm_call(
credentials=credentials,
llm_model=llm_model,
prompt=prompt,
compress_prompt_to_fit=input_data.compress_prompt_to_fit,
force_json_output=(
input_data.force_json_output
and bool(input_data.expected_format)
),
json_format=bool(input_data.expected_format),
ollama_host=input_data.ollama_host,
max_tokens=input_data.max_tokens,
)
@@ -975,55 +970,16 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
logger.debug(f"LLM attempt-{retry_count} response: {response_text}")
if input_data.expected_format:
try:
response_obj = self.get_json_from_response(
response_text,
pure_json_mode=input_data.force_json_output,
output_tag_start=output_tag_start,
)
except (ValueError, JSONDecodeError) as parse_error:
censored_response = re.sub(r"[A-Za-z0-9]", "*", response_text)
response_snippet = (
f"{censored_response[:50]}...{censored_response[-30:]}"
)
logger.warning(
f"Error getting JSON from LLM response: {parse_error}\n\n"
f"Response start+end: `{response_snippet}`"
)
prompt.append({"role": "assistant", "content": response_text})
error_feedback_message = self.invalid_response_feedback(
parse_error,
was_parseable=False,
list_mode=input_data.list_result,
pure_json_mode=input_data.force_json_output,
output_tag_start=output_tag_start,
)
prompt.append(
{"role": "user", "content": error_feedback_message}
)
continue
response_obj = json.loads(response_text)
# Handle object response for `force_json_output`+`list_result`
if input_data.list_result and isinstance(response_obj, dict):
if "results" in response_obj and isinstance(
response_obj["results"], list
):
response_obj = response_obj["results"]
else:
error_feedback_message = (
"Expected an array of objects in the 'results' key, "
f"but got: {response_obj}"
)
prompt.append(
{"role": "assistant", "content": response_text}
)
prompt.append(
{"role": "user", "content": error_feedback_message}
)
continue
if "results" in response_obj:
response_obj = response_obj.get("results", [])
elif len(response_obj) == 1:
response_obj = list(response_obj.values())
validation_errors = "\n".join(
response_error = "\n".join(
[
validation_error
for response_item in (
@@ -1035,7 +991,7 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
]
)
if not validation_errors:
if not response_error:
self.merge_stats(
NodeExecutionStats(
llm_call_count=retry_count + 1,
@@ -1045,16 +1001,6 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
yield "response", response_obj
yield "prompt", self.prompt
return
prompt.append({"role": "assistant", "content": response_text})
error_feedback_message = self.invalid_response_feedback(
validation_errors,
was_parseable=True,
list_mode=input_data.list_result,
pure_json_mode=input_data.force_json_output,
output_tag_start=output_tag_start,
)
prompt.append({"role": "user", "content": error_feedback_message})
else:
self.merge_stats(
NodeExecutionStats(
@@ -1065,6 +1011,21 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
yield "response", {"response": response_text}
yield "prompt", self.prompt
return
retry_prompt = trim_prompt(
f"""
|This is your previous error response:
|--
|{response_text}
|--
|
|And this is the error:
|--
|{response_error}
|--
"""
)
prompt.append({"role": "user", "content": retry_prompt})
except Exception as e:
logger.exception(f"Error calling LLM: {e}")
if (
@@ -1077,133 +1038,9 @@ class AIStructuredResponseGeneratorBlock(AIBlockBase):
logger.debug(
f"Reducing max_tokens to {input_data.max_tokens} for next attempt"
)
# Don't add retry prompt for token limit errors,
# just retry with lower maximum output tokens
retry_prompt = f"Error calling LLM: {e}"
error_feedback_message = f"Error calling LLM: {e}"
raise RuntimeError(error_feedback_message)
def response_format_instructions(
self,
expected_object_format: dict[str, str],
*,
list_mode: bool,
pure_json_mode: bool,
output_tag_start: str,
) -> str:
expected_output_format = json.dumps(expected_object_format, indent=2)
output_type = "object" if not list_mode else "array"
outer_output_type = "object" if pure_json_mode else output_type
if output_type == "array":
indented_obj_format = expected_output_format.replace("\n", "\n ")
expected_output_format = f"[\n {indented_obj_format},\n ...\n]"
if pure_json_mode:
indented_list_format = expected_output_format.replace("\n", "\n ")
expected_output_format = (
"{\n"
' "reasoning": "... (optional)",\n' # for better performance
f' "results": {indented_list_format}\n'
"}"
)
# Preserve indentation in prompt
expected_output_format = expected_output_format.replace("\n", "\n|")
# Prepare prompt
if not pure_json_mode:
expected_output_format = (
f"{output_tag_start}\n{expected_output_format}\n</json_output>"
)
instructions = f"""
|In your response you MUST include a valid JSON {outer_output_type} strictly following this format:
|{expected_output_format}
|
|If you cannot provide all the keys, you MUST provide an empty string for the values you cannot answer.
""".strip()
if not pure_json_mode:
instructions += f"""
|
|You MUST enclose your final JSON answer in {output_tag_start}...</json_output> tags, even if the user specifies a different tag.
|There MUST be exactly ONE {output_tag_start}...</json_output> block in your response, which MUST ONLY contain the JSON {outer_output_type} and nothing else. Other text outside this block is allowed.
""".strip()
return trim_prompt(instructions)
def invalid_response_feedback(
self,
error,
*,
was_parseable: bool,
list_mode: bool,
pure_json_mode: bool,
output_tag_start: str,
) -> str:
outer_output_type = "object" if not list_mode or pure_json_mode else "array"
if was_parseable:
complaint = f"Your previous response did not match the expected {outer_output_type} format."
else:
complaint = f"Your previous response did not contain a parseable JSON {outer_output_type}."
indented_parse_error = str(error).replace("\n", "\n|")
instruction = (
f"Please provide a {output_tag_start}...</json_output> block containing a"
if not pure_json_mode
else "Please provide a"
) + f" valid JSON {outer_output_type} that matches the expected format."
return trim_prompt(
f"""
|{complaint}
|
|{indented_parse_error}
|
|{instruction}
"""
)
def get_json_from_response(
self, response_text: str, *, pure_json_mode: bool, output_tag_start: str
) -> dict[str, Any] | list[dict[str, Any]]:
if pure_json_mode:
# Handle pure JSON responses
try:
return json.loads(response_text)
except JSONDecodeError as first_parse_error:
# If that didn't work, try finding the { and } to deal with possible ```json fences etc.
json_start = response_text.find("{")
json_end = response_text.rfind("}")
try:
return json.loads(response_text[json_start : json_end + 1])
except JSONDecodeError:
# Raise the original error, as it's more likely to be relevant
raise first_parse_error from None
if output_tag_start not in response_text:
raise ValueError(
"Response does not contain the expected "
f"{output_tag_start}...</json_output> block."
)
json_output = (
response_text.split(output_tag_start, 1)[1]
.rsplit("</json_output>", 1)[0]
.strip()
)
return json.loads(json_output)
def get_collision_proof_output_tag_id(self) -> str:
return secrets.token_hex(8)
def trim_prompt(s: str) -> str:
"""Removes indentation up to and including `|` from a multi-line prompt."""
lines = s.strip().split("\n")
return "\n".join([line.strip().lstrip("|") for line in lines])
raise RuntimeError(retry_prompt)
class AITextGeneratorBlock(AIBlockBase):

View File

@@ -1,536 +0,0 @@
"""
Notion API helper functions and client for making authenticated requests.
"""
from typing import Any, Dict, List, Optional
from backend.data.model import OAuth2Credentials
from backend.util.request import Requests
NOTION_VERSION = "2022-06-28"
class NotionAPIException(Exception):
"""Exception raised for Notion API errors."""
def __init__(self, message: str, status_code: int):
super().__init__(message)
self.status_code = status_code
class NotionClient:
"""Client for interacting with the Notion API."""
def __init__(self, credentials: OAuth2Credentials):
self.credentials = credentials
self.headers = {
"Authorization": credentials.auth_header(),
"Notion-Version": NOTION_VERSION,
"Content-Type": "application/json",
}
self.requests = Requests()
async def get_page(self, page_id: str) -> dict:
"""
Fetch a page by ID.
Args:
page_id: The ID of the page to fetch.
Returns:
The page object from Notion API.
"""
url = f"https://api.notion.com/v1/pages/{page_id}"
response = await self.requests.get(url, headers=self.headers)
if not response.ok:
raise NotionAPIException(
f"Failed to fetch page: {response.status} - {response.text()}",
response.status,
)
return response.json()
async def get_blocks(self, block_id: str, recursive: bool = True) -> List[dict]:
"""
Fetch all blocks from a page or block.
Args:
block_id: The ID of the page or block to fetch children from.
recursive: Whether to fetch nested blocks recursively.
Returns:
List of block objects.
"""
blocks = []
cursor = None
while True:
url = f"https://api.notion.com/v1/blocks/{block_id}/children"
params = {"page_size": 100}
if cursor:
params["start_cursor"] = cursor
response = await self.requests.get(url, headers=self.headers, params=params)
if not response.ok:
raise NotionAPIException(
f"Failed to fetch blocks: {response.status} - {response.text()}",
response.status,
)
data = response.json()
current_blocks = data.get("results", [])
# If recursive, fetch children for blocks that have them
if recursive:
for block in current_blocks:
if block.get("has_children"):
block["children"] = await self.get_blocks(
block["id"], recursive=True
)
blocks.extend(current_blocks)
if not data.get("has_more"):
break
cursor = data.get("next_cursor")
return blocks
async def query_database(
self,
database_id: str,
filter_obj: Optional[dict] = None,
sorts: Optional[List[dict]] = None,
page_size: int = 100,
) -> dict:
"""
Query a database with optional filters and sorts.
Args:
database_id: The ID of the database to query.
filter_obj: Optional filter object for the query.
sorts: Optional list of sort objects.
page_size: Number of results per page.
Returns:
Query results including pages and pagination info.
"""
url = f"https://api.notion.com/v1/databases/{database_id}/query"
payload: Dict[str, Any] = {"page_size": page_size}
if filter_obj:
payload["filter"] = filter_obj
if sorts:
payload["sorts"] = sorts
response = await self.requests.post(url, headers=self.headers, json=payload)
if not response.ok:
raise NotionAPIException(
f"Failed to query database: {response.status} - {response.text()}",
response.status,
)
return response.json()
async def create_page(
self,
parent: dict,
properties: dict,
children: Optional[List[dict]] = None,
icon: Optional[dict] = None,
cover: Optional[dict] = None,
) -> dict:
"""
Create a new page.
Args:
parent: Parent object (page_id or database_id).
properties: Page properties.
children: Optional list of block children.
icon: Optional icon object.
cover: Optional cover object.
Returns:
The created page object.
"""
url = "https://api.notion.com/v1/pages"
payload: Dict[str, Any] = {"parent": parent, "properties": properties}
if children:
payload["children"] = children
if icon:
payload["icon"] = icon
if cover:
payload["cover"] = cover
response = await self.requests.post(url, headers=self.headers, json=payload)
if not response.ok:
raise NotionAPIException(
f"Failed to create page: {response.status} - {response.text()}",
response.status,
)
return response.json()
async def update_page(self, page_id: str, properties: dict) -> dict:
"""
Update a page's properties.
Args:
page_id: The ID of the page to update.
properties: Properties to update.
Returns:
The updated page object.
"""
url = f"https://api.notion.com/v1/pages/{page_id}"
response = await self.requests.patch(
url, headers=self.headers, json={"properties": properties}
)
if not response.ok:
raise NotionAPIException(
f"Failed to update page: {response.status} - {response.text()}",
response.status,
)
return response.json()
async def append_blocks(self, block_id: str, children: List[dict]) -> dict:
"""
Append blocks to a page or block.
Args:
block_id: The ID of the page or block to append to.
children: List of block objects to append.
Returns:
Response with the created blocks.
"""
url = f"https://api.notion.com/v1/blocks/{block_id}/children"
response = await self.requests.patch(
url, headers=self.headers, json={"children": children}
)
if not response.ok:
raise NotionAPIException(
f"Failed to append blocks: {response.status} - {response.text()}",
response.status,
)
return response.json()
async def search(
self,
query: str = "",
filter_obj: Optional[dict] = None,
sort: Optional[dict] = None,
page_size: int = 100,
) -> dict:
"""
Search for pages and databases.
Args:
query: Search query text.
filter_obj: Optional filter object.
sort: Optional sort object.
page_size: Number of results per page.
Returns:
Search results.
"""
url = "https://api.notion.com/v1/search"
payload: Dict[str, Any] = {"page_size": page_size}
if query:
payload["query"] = query
if filter_obj:
payload["filter"] = filter_obj
if sort:
payload["sort"] = sort
response = await self.requests.post(url, headers=self.headers, json=payload)
if not response.ok:
raise NotionAPIException(
f"Search failed: {response.status} - {response.text()}", response.status
)
return response.json()
# Conversion helper functions
def parse_rich_text(rich_text_array: List[dict]) -> str:
"""
Extract plain text from a Notion rich text array.
Args:
rich_text_array: Array of rich text objects from Notion.
Returns:
Plain text string.
"""
if not rich_text_array:
return ""
text_parts = []
for text_obj in rich_text_array:
if "plain_text" in text_obj:
text_parts.append(text_obj["plain_text"])
return "".join(text_parts)
def rich_text_to_markdown(rich_text_array: List[dict]) -> str:
"""
Convert Notion rich text array to markdown with formatting.
Args:
rich_text_array: Array of rich text objects from Notion.
Returns:
Markdown formatted string.
"""
if not rich_text_array:
return ""
markdown_parts = []
for text_obj in rich_text_array:
text = text_obj.get("plain_text", "")
annotations = text_obj.get("annotations", {})
# Apply formatting based on annotations
if annotations.get("code"):
text = f"`{text}`"
else:
if annotations.get("bold"):
text = f"**{text}**"
if annotations.get("italic"):
text = f"*{text}*"
if annotations.get("strikethrough"):
text = f"~~{text}~~"
if annotations.get("underline"):
text = f"<u>{text}</u>"
# Handle links
if text_obj.get("href"):
text = f"[{text}]({text_obj['href']})"
markdown_parts.append(text)
return "".join(markdown_parts)
def block_to_markdown(block: dict, indent_level: int = 0) -> str:
"""
Convert a single Notion block to markdown.
Args:
block: Block object from Notion API.
indent_level: Current indentation level for nested blocks.
Returns:
Markdown string representation of the block.
"""
block_type = block.get("type")
indent = " " * indent_level
markdown_lines = []
# Handle different block types
if block_type == "paragraph":
text = rich_text_to_markdown(block["paragraph"].get("rich_text", []))
if text:
markdown_lines.append(f"{indent}{text}")
elif block_type == "heading_1":
text = parse_rich_text(block["heading_1"].get("rich_text", []))
markdown_lines.append(f"{indent}# {text}")
elif block_type == "heading_2":
text = parse_rich_text(block["heading_2"].get("rich_text", []))
markdown_lines.append(f"{indent}## {text}")
elif block_type == "heading_3":
text = parse_rich_text(block["heading_3"].get("rich_text", []))
markdown_lines.append(f"{indent}### {text}")
elif block_type == "bulleted_list_item":
text = rich_text_to_markdown(block["bulleted_list_item"].get("rich_text", []))
markdown_lines.append(f"{indent}- {text}")
elif block_type == "numbered_list_item":
text = rich_text_to_markdown(block["numbered_list_item"].get("rich_text", []))
# Note: This is simplified - proper numbering would need context
markdown_lines.append(f"{indent}1. {text}")
elif block_type == "to_do":
text = rich_text_to_markdown(block["to_do"].get("rich_text", []))
checked = "x" if block["to_do"].get("checked") else " "
markdown_lines.append(f"{indent}- [{checked}] {text}")
elif block_type == "toggle":
text = rich_text_to_markdown(block["toggle"].get("rich_text", []))
markdown_lines.append(f"{indent}<details>")
markdown_lines.append(f"{indent}<summary>{text}</summary>")
markdown_lines.append(f"{indent}")
# Process children if they exist
if block.get("children"):
for child in block["children"]:
child_markdown = block_to_markdown(child, indent_level + 1)
if child_markdown:
markdown_lines.append(child_markdown)
markdown_lines.append(f"{indent}</details>")
elif block_type == "code":
code = parse_rich_text(block["code"].get("rich_text", []))
language = block["code"].get("language", "")
markdown_lines.append(f"{indent}```{language}")
markdown_lines.append(f"{indent}{code}")
markdown_lines.append(f"{indent}```")
elif block_type == "quote":
text = rich_text_to_markdown(block["quote"].get("rich_text", []))
markdown_lines.append(f"{indent}> {text}")
elif block_type == "divider":
markdown_lines.append(f"{indent}---")
elif block_type == "image":
image = block["image"]
url = image.get("external", {}).get("url") or image.get("file", {}).get(
"url", ""
)
caption = parse_rich_text(image.get("caption", []))
alt_text = caption if caption else "Image"
markdown_lines.append(f"{indent}![{alt_text}]({url})")
if caption:
markdown_lines.append(f"{indent}*{caption}*")
elif block_type == "video":
video = block["video"]
url = video.get("external", {}).get("url") or video.get("file", {}).get(
"url", ""
)
caption = parse_rich_text(video.get("caption", []))
markdown_lines.append(f"{indent}[Video]({url})")
if caption:
markdown_lines.append(f"{indent}*{caption}*")
elif block_type == "file":
file = block["file"]
url = file.get("external", {}).get("url") or file.get("file", {}).get("url", "")
caption = parse_rich_text(file.get("caption", []))
name = caption if caption else "File"
markdown_lines.append(f"{indent}[{name}]({url})")
elif block_type == "bookmark":
url = block["bookmark"].get("url", "")
caption = parse_rich_text(block["bookmark"].get("caption", []))
markdown_lines.append(f"{indent}[{caption if caption else url}]({url})")
elif block_type == "equation":
expression = block["equation"].get("expression", "")
markdown_lines.append(f"{indent}$${expression}$$")
elif block_type == "callout":
text = rich_text_to_markdown(block["callout"].get("rich_text", []))
icon = block["callout"].get("icon", {})
if icon.get("emoji"):
markdown_lines.append(f"{indent}> {icon['emoji']} {text}")
else:
markdown_lines.append(f"{indent}> {text}")
elif block_type == "child_page":
title = block["child_page"].get("title", "Untitled")
markdown_lines.append(f"{indent}📄 [{title}](notion://page/{block['id']})")
elif block_type == "child_database":
title = block["child_database"].get("title", "Untitled Database")
markdown_lines.append(f"{indent}🗂️ [{title}](notion://database/{block['id']})")
elif block_type == "table":
# Tables are complex - for now just indicate there's a table
markdown_lines.append(
f"{indent}[Table with {block['table'].get('table_width', 0)} columns]"
)
elif block_type == "column_list":
# Process columns
if block.get("children"):
markdown_lines.append(f"{indent}<div style='display: flex'>")
for column in block["children"]:
markdown_lines.append(f"{indent}<div style='flex: 1'>")
if column.get("children"):
for child in column["children"]:
child_markdown = block_to_markdown(child, indent_level + 1)
if child_markdown:
markdown_lines.append(child_markdown)
markdown_lines.append(f"{indent}</div>")
markdown_lines.append(f"{indent}</div>")
# Handle children for blocks that haven't been processed yet
elif block.get("children") and block_type not in ["toggle", "column_list"]:
for child in block["children"]:
child_markdown = block_to_markdown(child, indent_level)
if child_markdown:
markdown_lines.append(child_markdown)
return "\n".join(markdown_lines) if markdown_lines else ""
def blocks_to_markdown(blocks: List[dict]) -> str:
"""
Convert a list of Notion blocks to a markdown document.
Args:
blocks: List of block objects from Notion API.
Returns:
Complete markdown document as a string.
"""
markdown_parts = []
for i, block in enumerate(blocks):
markdown = block_to_markdown(block)
if markdown:
markdown_parts.append(markdown)
# Add spacing between top-level blocks (except lists)
if i < len(blocks) - 1:
next_type = blocks[i + 1].get("type", "")
current_type = block.get("type", "")
# Don't add extra spacing between list items
list_types = {"bulleted_list_item", "numbered_list_item", "to_do"}
if not (current_type in list_types and next_type in list_types):
markdown_parts.append("")
return "\n".join(markdown_parts)
def extract_page_title(page: dict) -> str:
"""
Extract the title from a Notion page object.
Args:
page: Page object from Notion API.
Returns:
Page title as a string.
"""
properties = page.get("properties", {})
# Find the title property (it has type "title")
for prop_name, prop_value in properties.items():
if prop_value.get("type") == "title":
return parse_rich_text(prop_value.get("title", []))
return "Untitled"

View File

@@ -1,42 +0,0 @@
from typing import Literal
from pydantic import SecretStr
from backend.data.model import CredentialsField, CredentialsMetaInput, OAuth2Credentials
from backend.integrations.providers import ProviderName
from backend.util.settings import Secrets
secrets = Secrets()
NOTION_OAUTH_IS_CONFIGURED = bool(
secrets.notion_client_id and secrets.notion_client_secret
)
NotionCredentials = OAuth2Credentials
NotionCredentialsInput = CredentialsMetaInput[
Literal[ProviderName.NOTION], Literal["oauth2"]
]
def NotionCredentialsField() -> NotionCredentialsInput:
"""Creates a Notion OAuth2 credentials field."""
return CredentialsField(
description="Connect your Notion account. Ensure the pages/databases are shared with the integration."
)
# Test credentials for Notion OAuth2
TEST_CREDENTIALS = OAuth2Credentials(
id="01234567-89ab-cdef-0123-456789abcdef",
provider="notion",
access_token=SecretStr("test_access_token"),
title="Mock Notion OAuth",
scopes=["read_content", "insert_content", "update_content"],
username="testuser",
)
TEST_CREDENTIALS_INPUT = {
"provider": TEST_CREDENTIALS.provider,
"id": TEST_CREDENTIALS.id,
"type": TEST_CREDENTIALS.type,
"title": TEST_CREDENTIALS.title,
}

View File

@@ -1,360 +0,0 @@
from __future__ import annotations
from typing import Any, Dict, List, Optional
from pydantic import model_validator
from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
from backend.data.model import OAuth2Credentials, SchemaField
from ._api import NotionClient
from ._auth import (
NOTION_OAUTH_IS_CONFIGURED,
TEST_CREDENTIALS,
TEST_CREDENTIALS_INPUT,
NotionCredentialsField,
NotionCredentialsInput,
)
class NotionCreatePageBlock(Block):
"""Create a new page in Notion with content."""
class Input(BlockSchema):
credentials: NotionCredentialsInput = NotionCredentialsField()
parent_page_id: Optional[str] = SchemaField(
description="Parent page ID to create the page under. Either this OR parent_database_id is required.",
default=None,
)
parent_database_id: Optional[str] = SchemaField(
description="Parent database ID to create the page in. Either this OR parent_page_id is required.",
default=None,
)
title: str = SchemaField(
description="Title of the new page",
)
content: Optional[str] = SchemaField(
description="Content for the page. Can be plain text or markdown - will be converted to Notion blocks.",
default=None,
)
properties: Optional[Dict[str, Any]] = SchemaField(
description="Additional properties for database pages (e.g., {'Status': 'In Progress', 'Priority': 'High'})",
default=None,
)
icon_emoji: Optional[str] = SchemaField(
description="Emoji to use as the page icon (e.g., '📄', '🚀')", default=None
)
@model_validator(mode="after")
def validate_parent(self):
"""Ensure either parent_page_id or parent_database_id is provided."""
if not self.parent_page_id and not self.parent_database_id:
raise ValueError(
"Either parent_page_id or parent_database_id must be provided"
)
if self.parent_page_id and self.parent_database_id:
raise ValueError(
"Only one of parent_page_id or parent_database_id should be provided, not both"
)
return self
class Output(BlockSchema):
page_id: str = SchemaField(description="ID of the created page.")
page_url: str = SchemaField(description="URL of the created page.")
error: str = SchemaField(description="Error message if the operation failed.")
def __init__(self):
super().__init__(
id="c15febe0-66ce-4c6f-aebd-5ab351653804",
description="Create a new page in Notion. Requires EITHER a parent_page_id OR parent_database_id. Supports markdown content.",
categories={BlockCategory.PRODUCTIVITY},
input_schema=NotionCreatePageBlock.Input,
output_schema=NotionCreatePageBlock.Output,
disabled=not NOTION_OAUTH_IS_CONFIGURED,
test_input={
"parent_page_id": "00000000-0000-0000-0000-000000000000",
"title": "Test Page",
"content": "This is test content.",
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[
("page_id", "12345678-1234-1234-1234-123456789012"),
(
"page_url",
"https://notion.so/Test-Page-12345678123412341234123456789012",
),
],
test_credentials=TEST_CREDENTIALS,
test_mock={
"create_page": lambda *args, **kwargs: (
"12345678-1234-1234-1234-123456789012",
"https://notion.so/Test-Page-12345678123412341234123456789012",
)
},
)
@staticmethod
def _markdown_to_blocks(content: str) -> List[dict]:
"""Convert markdown content to Notion block objects."""
if not content:
return []
blocks = []
lines = content.split("\n")
i = 0
while i < len(lines):
line = lines[i]
# Skip empty lines
if not line.strip():
i += 1
continue
# Headings
if line.startswith("### "):
blocks.append(
{
"type": "heading_3",
"heading_3": {
"rich_text": [
{"type": "text", "text": {"content": line[4:].strip()}}
]
},
}
)
elif line.startswith("## "):
blocks.append(
{
"type": "heading_2",
"heading_2": {
"rich_text": [
{"type": "text", "text": {"content": line[3:].strip()}}
]
},
}
)
elif line.startswith("# "):
blocks.append(
{
"type": "heading_1",
"heading_1": {
"rich_text": [
{"type": "text", "text": {"content": line[2:].strip()}}
]
},
}
)
# Bullet points
elif line.strip().startswith("- "):
blocks.append(
{
"type": "bulleted_list_item",
"bulleted_list_item": {
"rich_text": [
{
"type": "text",
"text": {"content": line.strip()[2:].strip()},
}
]
},
}
)
# Numbered list
elif line.strip() and line.strip()[0].isdigit() and ". " in line:
content_start = line.find(". ") + 2
blocks.append(
{
"type": "numbered_list_item",
"numbered_list_item": {
"rich_text": [
{
"type": "text",
"text": {"content": line[content_start:].strip()},
}
]
},
}
)
# Code block
elif line.strip().startswith("```"):
code_lines = []
language = line[3:].strip() or "plain text"
i += 1
while i < len(lines) and not lines[i].strip().startswith("```"):
code_lines.append(lines[i])
i += 1
blocks.append(
{
"type": "code",
"code": {
"rich_text": [
{
"type": "text",
"text": {"content": "\n".join(code_lines)},
}
],
"language": language,
},
}
)
# Quote
elif line.strip().startswith("> "):
blocks.append(
{
"type": "quote",
"quote": {
"rich_text": [
{
"type": "text",
"text": {"content": line.strip()[2:].strip()},
}
]
},
}
)
# Horizontal rule
elif line.strip() in ["---", "***", "___"]:
blocks.append({"type": "divider", "divider": {}})
# Regular paragraph
else:
# Parse for basic markdown formatting
text_content = line.strip()
rich_text = []
# Simple bold/italic parsing (this is simplified)
if "**" in text_content or "*" in text_content:
# For now, just pass as plain text
# A full implementation would parse and create proper annotations
rich_text = [{"type": "text", "text": {"content": text_content}}]
else:
rich_text = [{"type": "text", "text": {"content": text_content}}]
blocks.append(
{"type": "paragraph", "paragraph": {"rich_text": rich_text}}
)
i += 1
return blocks
@staticmethod
def _build_properties(
title: str, additional_properties: Optional[Dict[str, Any]] = None
) -> Dict[str, Any]:
"""Build properties object for page creation."""
properties: Dict[str, Any] = {
"title": {"title": [{"type": "text", "text": {"content": title}}]}
}
if additional_properties:
for key, value in additional_properties.items():
if key.lower() == "title":
continue # Skip title as we already have it
# Try to intelligently map property types
if isinstance(value, bool):
properties[key] = {"checkbox": value}
elif isinstance(value, (int, float)):
properties[key] = {"number": value}
elif isinstance(value, list):
# Assume multi-select
properties[key] = {
"multi_select": [{"name": str(item)} for item in value]
}
elif isinstance(value, str):
# Could be select, rich_text, or other types
# For simplicity, try common patterns
if key.lower() in ["status", "priority", "type", "category"]:
properties[key] = {"select": {"name": value}}
elif key.lower() in ["url", "link"]:
properties[key] = {"url": value}
elif key.lower() in ["email"]:
properties[key] = {"email": value}
else:
properties[key] = {
"rich_text": [{"type": "text", "text": {"content": value}}]
}
return properties
@staticmethod
async def create_page(
credentials: OAuth2Credentials,
title: str,
parent_page_id: Optional[str] = None,
parent_database_id: Optional[str] = None,
content: Optional[str] = None,
properties: Optional[Dict[str, Any]] = None,
icon_emoji: Optional[str] = None,
) -> tuple[str, str]:
"""
Create a new Notion page.
Returns:
Tuple of (page_id, page_url)
"""
if not parent_page_id and not parent_database_id:
raise ValueError(
"Either parent_page_id or parent_database_id must be provided"
)
if parent_page_id and parent_database_id:
raise ValueError(
"Only one of parent_page_id or parent_database_id should be provided, not both"
)
client = NotionClient(credentials)
# Build parent object
if parent_page_id:
parent = {"type": "page_id", "page_id": parent_page_id}
else:
parent = {"type": "database_id", "database_id": parent_database_id}
# Build properties
page_properties = NotionCreatePageBlock._build_properties(title, properties)
# Convert content to blocks if provided
children = None
if content:
children = NotionCreatePageBlock._markdown_to_blocks(content)
# Build icon if provided
icon = None
if icon_emoji:
icon = {"type": "emoji", "emoji": icon_emoji}
# Create the page
result = await client.create_page(
parent=parent, properties=page_properties, children=children, icon=icon
)
page_id = result.get("id", "")
page_url = result.get("url", "")
if not page_id or not page_url:
raise ValueError("Failed to get page ID or URL from Notion response")
return page_id, page_url
async def run(
self,
input_data: Input,
*,
credentials: OAuth2Credentials,
**kwargs,
) -> BlockOutput:
try:
page_id, page_url = await self.create_page(
credentials,
input_data.title,
input_data.parent_page_id,
input_data.parent_database_id,
input_data.content,
input_data.properties,
input_data.icon_emoji,
)
yield "page_id", page_id
yield "page_url", page_url
except Exception as e:
yield "error", str(e) if str(e) else "Unknown error"

View File

@@ -1,285 +0,0 @@
from __future__ import annotations
from typing import Any, Dict, List, Optional
from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
from backend.data.model import OAuth2Credentials, SchemaField
from ._api import NotionClient, parse_rich_text
from ._auth import (
NOTION_OAUTH_IS_CONFIGURED,
TEST_CREDENTIALS,
TEST_CREDENTIALS_INPUT,
NotionCredentialsField,
NotionCredentialsInput,
)
class NotionReadDatabaseBlock(Block):
"""Query a Notion database and retrieve entries with their properties."""
class Input(BlockSchema):
credentials: NotionCredentialsInput = NotionCredentialsField()
database_id: str = SchemaField(
description="Notion database ID. Must be accessible by the connected integration.",
)
filter_property: Optional[str] = SchemaField(
description="Property name to filter by (e.g., 'Status', 'Priority')",
default=None,
)
filter_value: Optional[str] = SchemaField(
description="Value to filter for in the specified property", default=None
)
sort_property: Optional[str] = SchemaField(
description="Property name to sort by", default=None
)
sort_direction: Optional[str] = SchemaField(
description="Sort direction: 'ascending' or 'descending'",
default="ascending",
)
limit: int = SchemaField(
description="Maximum number of entries to retrieve",
default=100,
ge=1,
le=100,
)
class Output(BlockSchema):
entries: List[Dict[str, Any]] = SchemaField(
description="List of database entries with their properties."
)
entry: Dict[str, Any] = SchemaField(
description="Individual database entry (yields one per entry found)."
)
entry_ids: List[str] = SchemaField(
description="List of entry IDs for batch operations."
)
entry_id: str = SchemaField(
description="Individual entry ID (yields one per entry found)."
)
count: int = SchemaField(description="Number of entries retrieved.")
database_title: str = SchemaField(description="Title of the database.")
error: str = SchemaField(description="Error message if the operation failed.")
def __init__(self):
super().__init__(
id="fcd53135-88c9-4ba3-be50-cc6936286e6c",
description="Query a Notion database with optional filtering and sorting, returning structured entries.",
categories={BlockCategory.PRODUCTIVITY},
input_schema=NotionReadDatabaseBlock.Input,
output_schema=NotionReadDatabaseBlock.Output,
disabled=not NOTION_OAUTH_IS_CONFIGURED,
test_input={
"database_id": "00000000-0000-0000-0000-000000000000",
"limit": 10,
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[
(
"entries",
[{"Name": "Test Entry", "Status": "Active", "_id": "test-123"}],
),
("entry_ids", ["test-123"]),
(
"entry",
{"Name": "Test Entry", "Status": "Active", "_id": "test-123"},
),
("entry_id", "test-123"),
("count", 1),
("database_title", "Test Database"),
],
test_credentials=TEST_CREDENTIALS,
test_mock={
"query_database": lambda *args, **kwargs: (
[{"Name": "Test Entry", "Status": "Active", "_id": "test-123"}],
1,
"Test Database",
)
},
)
@staticmethod
def _parse_property_value(prop: dict) -> Any:
"""Parse a Notion property value into a simple Python type."""
prop_type = prop.get("type")
if prop_type == "title":
return parse_rich_text(prop.get("title", []))
elif prop_type == "rich_text":
return parse_rich_text(prop.get("rich_text", []))
elif prop_type == "number":
return prop.get("number")
elif prop_type == "select":
select = prop.get("select")
return select.get("name") if select else None
elif prop_type == "multi_select":
return [item.get("name") for item in prop.get("multi_select", [])]
elif prop_type == "date":
date = prop.get("date")
if date:
return date.get("start")
return None
elif prop_type == "checkbox":
return prop.get("checkbox", False)
elif prop_type == "url":
return prop.get("url")
elif prop_type == "email":
return prop.get("email")
elif prop_type == "phone_number":
return prop.get("phone_number")
elif prop_type == "people":
return [
person.get("name", person.get("id"))
for person in prop.get("people", [])
]
elif prop_type == "files":
files = prop.get("files", [])
return [
f.get(
"name",
f.get("external", {}).get("url", f.get("file", {}).get("url")),
)
for f in files
]
elif prop_type == "relation":
return [rel.get("id") for rel in prop.get("relation", [])]
elif prop_type == "formula":
formula = prop.get("formula", {})
return formula.get(formula.get("type"))
elif prop_type == "rollup":
rollup = prop.get("rollup", {})
return rollup.get(rollup.get("type"))
elif prop_type == "created_time":
return prop.get("created_time")
elif prop_type == "created_by":
return prop.get("created_by", {}).get(
"name", prop.get("created_by", {}).get("id")
)
elif prop_type == "last_edited_time":
return prop.get("last_edited_time")
elif prop_type == "last_edited_by":
return prop.get("last_edited_by", {}).get(
"name", prop.get("last_edited_by", {}).get("id")
)
else:
# Return the raw value for unknown types
return prop
@staticmethod
def _build_filter(property_name: str, value: str) -> dict:
"""Build a simple filter object for a property."""
# This is a simplified filter - in reality, you'd need to know the property type
# For now, we'll try common filter types
return {
"or": [
{"property": property_name, "rich_text": {"contains": value}},
{"property": property_name, "title": {"contains": value}},
{"property": property_name, "select": {"equals": value}},
{"property": property_name, "multi_select": {"contains": value}},
]
}
@staticmethod
async def query_database(
credentials: OAuth2Credentials,
database_id: str,
filter_property: Optional[str] = None,
filter_value: Optional[str] = None,
sort_property: Optional[str] = None,
sort_direction: str = "ascending",
limit: int = 100,
) -> tuple[List[Dict[str, Any]], int, str]:
"""
Query a Notion database and parse the results.
Returns:
Tuple of (entries_list, count, database_title)
"""
client = NotionClient(credentials)
# Build filter if specified
filter_obj = None
if filter_property and filter_value:
filter_obj = NotionReadDatabaseBlock._build_filter(
filter_property, filter_value
)
# Build sorts if specified
sorts = None
if sort_property:
sorts = [{"property": sort_property, "direction": sort_direction}]
# Query the database
result = await client.query_database(
database_id, filter_obj=filter_obj, sorts=sorts, page_size=limit
)
# Parse the entries
entries = []
for page in result.get("results", []):
entry = {}
properties = page.get("properties", {})
for prop_name, prop_value in properties.items():
entry[prop_name] = NotionReadDatabaseBlock._parse_property_value(
prop_value
)
# Add metadata
entry["_id"] = page.get("id")
entry["_url"] = page.get("url")
entry["_created_time"] = page.get("created_time")
entry["_last_edited_time"] = page.get("last_edited_time")
entries.append(entry)
# Get database title (we need to make a separate call for this)
try:
database_url = f"https://api.notion.com/v1/databases/{database_id}"
db_response = await client.requests.get(
database_url, headers=client.headers
)
if db_response.ok:
db_data = db_response.json()
db_title = parse_rich_text(db_data.get("title", []))
else:
db_title = "Unknown Database"
except Exception:
db_title = "Unknown Database"
return entries, len(entries), db_title
async def run(
self,
input_data: Input,
*,
credentials: OAuth2Credentials,
**kwargs,
) -> BlockOutput:
try:
entries, count, db_title = await self.query_database(
credentials,
input_data.database_id,
input_data.filter_property,
input_data.filter_value,
input_data.sort_property,
input_data.sort_direction or "ascending",
input_data.limit,
)
# Yield the complete list for batch operations
yield "entries", entries
# Extract and yield IDs as a list for batch operations
entry_ids = [entry["_id"] for entry in entries if "_id" in entry]
yield "entry_ids", entry_ids
# Yield each individual entry and its ID for single connections
for entry in entries:
yield "entry", entry
if "_id" in entry:
yield "entry_id", entry["_id"]
yield "count", count
yield "database_title", db_title
except Exception as e:
yield "error", str(e) if str(e) else "Unknown error"

View File

@@ -1,64 +0,0 @@
from __future__ import annotations
from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
from backend.data.model import OAuth2Credentials, SchemaField
from ._api import NotionClient
from ._auth import (
NOTION_OAUTH_IS_CONFIGURED,
TEST_CREDENTIALS,
TEST_CREDENTIALS_INPUT,
NotionCredentialsField,
NotionCredentialsInput,
)
class NotionReadPageBlock(Block):
"""Read a Notion page by ID and return its raw JSON."""
class Input(BlockSchema):
credentials: NotionCredentialsInput = NotionCredentialsField()
page_id: str = SchemaField(
description="Notion page ID. Must be accessible by the connected integration. You can get this from the page URL notion.so/A-Page-586edd711467478da59fe3ce29a1ffab would be 586edd711467478da59fe35e29a1ffab",
)
class Output(BlockSchema):
page: dict = SchemaField(description="Raw Notion page JSON.")
error: str = SchemaField(description="Error message if the operation failed.")
def __init__(self):
super().__init__(
id="5246cc1d-34b7-452b-8fc5-3fb25fd8f542",
description="Read a Notion page by its ID and return its raw JSON.",
categories={BlockCategory.PRODUCTIVITY},
input_schema=NotionReadPageBlock.Input,
output_schema=NotionReadPageBlock.Output,
disabled=not NOTION_OAUTH_IS_CONFIGURED,
test_input={
"page_id": "00000000-0000-0000-0000-000000000000",
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[("page", dict)],
test_credentials=TEST_CREDENTIALS,
test_mock={
"get_page": lambda *args, **kwargs: {"object": "page", "id": "mocked"}
},
)
@staticmethod
async def get_page(credentials: OAuth2Credentials, page_id: str) -> dict:
client = NotionClient(credentials)
return await client.get_page(page_id)
async def run(
self,
input_data: Input,
*,
credentials: OAuth2Credentials,
**kwargs,
) -> BlockOutput:
try:
page = await self.get_page(credentials, input_data.page_id)
yield "page", page
except Exception as e:
yield "error", str(e) if str(e) else "Unknown error"

View File

@@ -1,109 +0,0 @@
from __future__ import annotations
from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
from backend.data.model import OAuth2Credentials, SchemaField
from ._api import NotionClient, blocks_to_markdown, extract_page_title
from ._auth import (
NOTION_OAUTH_IS_CONFIGURED,
TEST_CREDENTIALS,
TEST_CREDENTIALS_INPUT,
NotionCredentialsField,
NotionCredentialsInput,
)
class NotionReadPageMarkdownBlock(Block):
"""Read a Notion page and convert it to clean Markdown format."""
class Input(BlockSchema):
credentials: NotionCredentialsInput = NotionCredentialsField()
page_id: str = SchemaField(
description="Notion page ID. Must be accessible by the connected integration. You can get this from the page URL notion.so/A-Page-586edd711467478da59fe35e29a1ffab would be 586edd711467478da59fe35e29a1ffab",
)
include_title: bool = SchemaField(
description="Whether to include the page title as a header in the markdown",
default=True,
)
class Output(BlockSchema):
markdown: str = SchemaField(description="Page content in Markdown format.")
title: str = SchemaField(description="Page title.")
error: str = SchemaField(description="Error message if the operation failed.")
def __init__(self):
super().__init__(
id="d1312c4d-fae2-4e70-893d-f4d07cce1d4e",
description="Read a Notion page and convert it to Markdown format with proper formatting for headings, lists, links, and rich text.",
categories={BlockCategory.PRODUCTIVITY},
input_schema=NotionReadPageMarkdownBlock.Input,
output_schema=NotionReadPageMarkdownBlock.Output,
disabled=not NOTION_OAUTH_IS_CONFIGURED,
test_input={
"page_id": "00000000-0000-0000-0000-000000000000",
"include_title": True,
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[
("markdown", "# Test Page\n\nThis is test content."),
("title", "Test Page"),
],
test_credentials=TEST_CREDENTIALS,
test_mock={
"get_page_markdown": lambda *args, **kwargs: (
"# Test Page\n\nThis is test content.",
"Test Page",
)
},
)
@staticmethod
async def get_page_markdown(
credentials: OAuth2Credentials, page_id: str, include_title: bool = True
) -> tuple[str, str]:
"""
Get a Notion page and convert it to markdown.
Args:
credentials: OAuth2 credentials for Notion.
page_id: The ID of the page to fetch.
include_title: Whether to include the page title in the markdown.
Returns:
Tuple of (markdown_content, title)
"""
client = NotionClient(credentials)
# Get page metadata
page = await client.get_page(page_id)
title = extract_page_title(page)
# Get all blocks from the page
blocks = await client.get_blocks(page_id, recursive=True)
# Convert blocks to markdown
content_markdown = blocks_to_markdown(blocks)
# Combine title and content if requested
if include_title and title:
full_markdown = f"# {title}\n\n{content_markdown}"
else:
full_markdown = content_markdown
return full_markdown, title
async def run(
self,
input_data: Input,
*,
credentials: OAuth2Credentials,
**kwargs,
) -> BlockOutput:
try:
markdown, title = await self.get_page_markdown(
credentials, input_data.page_id, input_data.include_title
)
yield "markdown", markdown
yield "title", title
except Exception as e:
yield "error", str(e) if str(e) else "Unknown error"

View File

@@ -1,225 +0,0 @@
from __future__ import annotations
from typing import List, Optional
from pydantic import BaseModel
from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
from backend.data.model import OAuth2Credentials, SchemaField
from ._api import NotionClient, extract_page_title, parse_rich_text
from ._auth import (
NOTION_OAUTH_IS_CONFIGURED,
TEST_CREDENTIALS,
TEST_CREDENTIALS_INPUT,
NotionCredentialsField,
NotionCredentialsInput,
)
class NotionSearchResult(BaseModel):
"""Typed model for Notion search results."""
id: str
type: str # 'page' or 'database'
title: str
url: str
created_time: Optional[str] = None
last_edited_time: Optional[str] = None
parent_type: Optional[str] = None # 'page', 'database', or 'workspace'
parent_id: Optional[str] = None
icon: Optional[str] = None # emoji icon if present
is_inline: Optional[bool] = None # for databases only
class NotionSearchBlock(Block):
"""Search across your Notion workspace for pages and databases."""
class Input(BlockSchema):
credentials: NotionCredentialsInput = NotionCredentialsField()
query: str = SchemaField(
description="Search query text. Leave empty to get all accessible pages/databases.",
default="",
)
filter_type: Optional[str] = SchemaField(
description="Filter results by type: 'page' or 'database'. Leave empty for both.",
default=None,
)
limit: int = SchemaField(
description="Maximum number of results to return", default=20, ge=1, le=100
)
class Output(BlockSchema):
results: List[NotionSearchResult] = SchemaField(
description="List of search results with title, type, URL, and metadata."
)
result: NotionSearchResult = SchemaField(
description="Individual search result (yields one per result found)."
)
result_ids: List[str] = SchemaField(
description="List of IDs from search results for batch operations."
)
count: int = SchemaField(description="Number of results found.")
error: str = SchemaField(description="Error message if the operation failed.")
def __init__(self):
super().__init__(
id="313515dd-9848-46ea-9cd6-3c627c892c56",
description="Search your Notion workspace for pages and databases by text query.",
categories={BlockCategory.PRODUCTIVITY, BlockCategory.SEARCH},
input_schema=NotionSearchBlock.Input,
output_schema=NotionSearchBlock.Output,
disabled=not NOTION_OAUTH_IS_CONFIGURED,
test_input={
"query": "project",
"limit": 5,
"credentials": TEST_CREDENTIALS_INPUT,
},
test_output=[
(
"results",
[
NotionSearchResult(
id="123",
type="page",
title="Project Plan",
url="https://notion.so/Project-Plan-123",
)
],
),
("result_ids", ["123"]),
(
"result",
NotionSearchResult(
id="123",
type="page",
title="Project Plan",
url="https://notion.so/Project-Plan-123",
),
),
("count", 1),
],
test_credentials=TEST_CREDENTIALS,
test_mock={
"search_workspace": lambda *args, **kwargs: (
[
NotionSearchResult(
id="123",
type="page",
title="Project Plan",
url="https://notion.so/Project-Plan-123",
)
],
1,
)
},
)
@staticmethod
async def search_workspace(
credentials: OAuth2Credentials,
query: str = "",
filter_type: Optional[str] = None,
limit: int = 20,
) -> tuple[List[NotionSearchResult], int]:
"""
Search the Notion workspace.
Returns:
Tuple of (results_list, count)
"""
client = NotionClient(credentials)
# Build filter if type is specified
filter_obj = None
if filter_type:
filter_obj = {"property": "object", "value": filter_type}
# Execute search
response = await client.search(
query=query, filter_obj=filter_obj, page_size=limit
)
# Parse results
results = []
for item in response.get("results", []):
result_data = {
"id": item.get("id", ""),
"type": item.get("object", ""),
"url": item.get("url", ""),
"created_time": item.get("created_time"),
"last_edited_time": item.get("last_edited_time"),
"title": "", # Will be set below
}
# Extract title based on type
if item.get("object") == "page":
# For pages, get the title from properties
result_data["title"] = extract_page_title(item)
# Add parent info
parent = item.get("parent", {})
if parent.get("type") == "page_id":
result_data["parent_type"] = "page"
result_data["parent_id"] = parent.get("page_id")
elif parent.get("type") == "database_id":
result_data["parent_type"] = "database"
result_data["parent_id"] = parent.get("database_id")
elif parent.get("type") == "workspace":
result_data["parent_type"] = "workspace"
# Add icon if present
icon = item.get("icon")
if icon and icon.get("type") == "emoji":
result_data["icon"] = icon.get("emoji")
elif item.get("object") == "database":
# For databases, get title from the title array
result_data["title"] = parse_rich_text(item.get("title", []))
# Add database-specific metadata
result_data["is_inline"] = item.get("is_inline", False)
# Add parent info
parent = item.get("parent", {})
if parent.get("type") == "page_id":
result_data["parent_type"] = "page"
result_data["parent_id"] = parent.get("page_id")
elif parent.get("type") == "workspace":
result_data["parent_type"] = "workspace"
# Add icon if present
icon = item.get("icon")
if icon and icon.get("type") == "emoji":
result_data["icon"] = icon.get("emoji")
results.append(NotionSearchResult(**result_data))
return results, len(results)
async def run(
self,
input_data: Input,
*,
credentials: OAuth2Credentials,
**kwargs,
) -> BlockOutput:
try:
results, count = await self.search_workspace(
credentials, input_data.query, input_data.filter_type, input_data.limit
)
# Yield the complete list for batch operations
yield "results", results
# Extract and yield IDs as a list for batch operations
result_ids = [r.id for r in results]
yield "result_ids", result_ids
# Yield each individual result for single connections
for result in results:
yield "result", result
yield "count", count
except Exception as e:
yield "error", str(e) if str(e) else "Unknown error"

View File

@@ -523,6 +523,7 @@ class SmartDecisionMakerBlock(Block):
credentials=credentials,
llm_model=input_data.model,
prompt=prompt,
json_format=False,
max_tokens=input_data.max_tokens,
tools=tool_functions,
ollama_host=input_data.ollama_host,

View File

@@ -30,6 +30,7 @@ class TestLLMStatsTracking:
credentials=llm.TEST_CREDENTIALS,
llm_model=llm.LlmModel.GPT4O,
prompt=[{"role": "user", "content": "Hello"}],
json_format=False,
max_tokens=100,
)
@@ -41,8 +42,6 @@ class TestLLMStatsTracking:
@pytest.mark.asyncio
async def test_ai_structured_response_block_tracks_stats(self):
"""Test that AIStructuredResponseGeneratorBlock correctly tracks stats."""
from unittest.mock import patch
import backend.blocks.llm as llm
block = llm.AIStructuredResponseGeneratorBlock()
@@ -52,7 +51,7 @@ class TestLLMStatsTracking:
return llm.LLMResponse(
raw_response="",
prompt=[],
response='<json_output id="test123456">{"key1": "value1", "key2": "value2"}</json_output>',
response='{"key1": "value1", "key2": "value2"}',
tool_calls=None,
prompt_tokens=15,
completion_tokens=25,
@@ -70,12 +69,10 @@ class TestLLMStatsTracking:
)
outputs = {}
# Mock secrets.token_hex to return consistent ID
with patch("secrets.token_hex", return_value="test123456"):
async for output_name, output_data in block.run(
input_data, credentials=llm.TEST_CREDENTIALS
):
outputs[output_name] = output_data
async for output_name, output_data in block.run(
input_data, credentials=llm.TEST_CREDENTIALS
):
outputs[output_name] = output_data
# Check stats
assert block.execution_stats.input_token_count == 15
@@ -146,7 +143,7 @@ class TestLLMStatsTracking:
return llm.LLMResponse(
raw_response="",
prompt=[],
response='<json_output id="test123456">{"wrong": "format"}</json_output>',
response='{"wrong": "format"}',
tool_calls=None,
prompt_tokens=10,
completion_tokens=15,
@@ -157,7 +154,7 @@ class TestLLMStatsTracking:
return llm.LLMResponse(
raw_response="",
prompt=[],
response='<json_output id="test123456">{"key1": "value1", "key2": "value2"}</json_output>',
response='{"key1": "value1", "key2": "value2"}',
tool_calls=None,
prompt_tokens=20,
completion_tokens=25,
@@ -176,12 +173,10 @@ class TestLLMStatsTracking:
)
outputs = {}
# Mock secrets.token_hex to return consistent ID
with patch("secrets.token_hex", return_value="test123456"):
async for output_name, output_data in block.run(
input_data, credentials=llm.TEST_CREDENTIALS
):
outputs[output_name] = output_data
async for output_name, output_data in block.run(
input_data, credentials=llm.TEST_CREDENTIALS
):
outputs[output_name] = output_data
# Check stats - should accumulate both calls
# For 2 attempts: attempt 1 (failed) + attempt 2 (success) = 2 total
@@ -274,8 +269,7 @@ class TestLLMStatsTracking:
mock_response.choices = [
MagicMock(
message=MagicMock(
content='<json_output id="test123456">{"summary": "Test chunk summary"}</json_output>',
tool_calls=None,
content='{"summary": "Test chunk summary"}', tool_calls=None
)
)
]
@@ -283,7 +277,7 @@ class TestLLMStatsTracking:
mock_response.choices = [
MagicMock(
message=MagicMock(
content='<json_output id="test123456">{"final_summary": "Test final summary"}</json_output>',
content='{"final_summary": "Test final summary"}',
tool_calls=None,
)
)
@@ -304,13 +298,11 @@ class TestLLMStatsTracking:
max_tokens=1000, # Large enough to avoid chunking
)
# Mock secrets.token_hex to return consistent ID
with patch("secrets.token_hex", return_value="test123456"):
outputs = {}
async for output_name, output_data in block.run(
input_data, credentials=llm.TEST_CREDENTIALS
):
outputs[output_name] = output_data
outputs = {}
async for output_name, output_data in block.run(
input_data, credentials=llm.TEST_CREDENTIALS
):
outputs[output_name] = output_data
print(f"Actual calls made: {call_count}")
print(f"Block stats: {block.execution_stats}")
@@ -465,7 +457,7 @@ class TestLLMStatsTracking:
return llm.LLMResponse(
raw_response="",
prompt=[],
response='<json_output id="test123456">{"result": "test"}</json_output>',
response='{"result": "test"}',
tool_calls=None,
prompt_tokens=10,
completion_tokens=20,
@@ -484,12 +476,10 @@ class TestLLMStatsTracking:
# Run the block
outputs = {}
# Mock secrets.token_hex to return consistent ID
with patch("secrets.token_hex", return_value="test123456"):
async for output_name, output_data in block.run(
input_data, credentials=llm.TEST_CREDENTIALS
):
outputs[output_name] = output_data
async for output_name, output_data in block.run(
input_data, credentials=llm.TEST_CREDENTIALS
):
outputs[output_name] = output_data
# Block finished - now grab and assert stats
assert block.execution_stats is not None

View File

@@ -172,11 +172,6 @@ class FillTextTemplateBlock(Block):
format: str = SchemaField(
description="Template to format the text using `values`. Use Jinja2 syntax."
)
escape_html: bool = SchemaField(
default=False,
advanced=True,
description="Whether to escape special characters in the inserted values to be HTML-safe. Enable for HTML output, disable for plain text.",
)
class Output(BlockSchema):
output: str = SchemaField(description="Formatted text")
@@ -210,7 +205,6 @@ class FillTextTemplateBlock(Block):
)
async def run(self, input_data: Input, **kwargs) -> BlockOutput:
formatter = text.TextFormatter(autoescape=input_data.escape_html)
yield "output", formatter.format_string(input_data.format, input_data.values)

View File

@@ -1,3 +1,4 @@
import functools
import inspect
import logging
import os
@@ -20,7 +21,6 @@ from typing import (
import jsonref
import jsonschema
from autogpt_libs.utils.cache import cached
from prisma.models import AgentBlock
from prisma.types import AgentBlockCreateInput
from pydantic import BaseModel
@@ -722,7 +722,7 @@ def get_block(block_id: str) -> Block[BlockSchema, BlockSchema] | None:
return cls() if cls else None
@cached()
@functools.cache
def get_webhook_block_ids() -> Sequence[str]:
return [
id
@@ -731,7 +731,7 @@ def get_webhook_block_ids() -> Sequence[str]:
]
@cached()
@functools.cache
def get_io_block_ids() -> Sequence[str]:
return [
id

View File

@@ -83,7 +83,7 @@ async def disconnect():
# Transaction timeout constant (in milliseconds)
TRANSACTION_TIMEOUT = 30000 # 30 seconds - Increased from 15s to prevent timeout errors during graph creation under load
TRANSACTION_TIMEOUT = 15000 # 15 seconds - Increased from 5s to prevent timeout errors
@asynccontextmanager

View File

@@ -92,31 +92,6 @@ ExecutionStatus = AgentExecutionStatus
NodeInputMask = Mapping[str, JsonValue]
NodesInputMasks = Mapping[str, NodeInputMask]
# dest: source
VALID_STATUS_TRANSITIONS = {
ExecutionStatus.QUEUED: [
ExecutionStatus.INCOMPLETE,
],
ExecutionStatus.RUNNING: [
ExecutionStatus.INCOMPLETE,
ExecutionStatus.QUEUED,
ExecutionStatus.TERMINATED, # For resuming halted execution
],
ExecutionStatus.COMPLETED: [
ExecutionStatus.RUNNING,
],
ExecutionStatus.FAILED: [
ExecutionStatus.INCOMPLETE,
ExecutionStatus.QUEUED,
ExecutionStatus.RUNNING,
],
ExecutionStatus.TERMINATED: [
ExecutionStatus.INCOMPLETE,
ExecutionStatus.QUEUED,
ExecutionStatus.RUNNING,
],
}
class GraphExecutionMeta(BaseDbModel):
id: str # type: ignore # Override base class to make this required
@@ -130,8 +105,6 @@ class GraphExecutionMeta(BaseDbModel):
status: ExecutionStatus
started_at: datetime
ended_at: datetime
is_shared: bool = False
share_token: Optional[str] = None
class Stats(BaseModel):
model_config = ConfigDict(
@@ -248,8 +221,6 @@ class GraphExecutionMeta(BaseDbModel):
if stats
else None
),
is_shared=_graph_exec.isShared,
share_token=_graph_exec.shareToken,
)
@@ -609,7 +580,7 @@ async def create_graph_execution(
data={
"agentGraphId": graph_id,
"agentGraphVersion": graph_version,
"executionStatus": ExecutionStatus.INCOMPLETE,
"executionStatus": ExecutionStatus.QUEUED,
"inputs": SafeJson(inputs),
"credentialInputs": (
SafeJson(credential_inputs) if credential_inputs else Json({})
@@ -756,11 +727,6 @@ async def update_graph_execution_stats(
status: ExecutionStatus | None = None,
stats: GraphExecutionStats | None = None,
) -> GraphExecution | None:
if not status and not stats:
raise ValueError(
f"Must provide either status or stats to update for execution {graph_exec_id}"
)
update_data: AgentGraphExecutionUpdateManyMutationInput = {}
if stats:
@@ -772,25 +738,20 @@ async def update_graph_execution_stats(
if status:
update_data["executionStatus"] = status
where_clause: AgentGraphExecutionWhereInput = {"id": graph_exec_id}
if status:
if allowed_from := VALID_STATUS_TRANSITIONS.get(status, []):
# Add OR clause to check if current status is one of the allowed source statuses
where_clause["AND"] = [
{"id": graph_exec_id},
{"OR": [{"executionStatus": s} for s in allowed_from]},
]
else:
raise ValueError(
f"Status {status} cannot be set via update for execution {graph_exec_id}. "
f"This status can only be set at creation or is not a valid target status."
)
await AgentGraphExecution.prisma().update_many(
where=where_clause,
updated_count = await AgentGraphExecution.prisma().update_many(
where={
"id": graph_exec_id,
"OR": [
{"executionStatus": ExecutionStatus.RUNNING},
{"executionStatus": ExecutionStatus.QUEUED},
# Terminated graph can be resumed.
{"executionStatus": ExecutionStatus.TERMINATED},
],
},
data=update_data,
)
if updated_count == 0:
return None
graph_exec = await AgentGraphExecution.prisma().find_unique_or_raise(
where={"id": graph_exec_id},
@@ -798,7 +759,6 @@ async def update_graph_execution_stats(
[*get_io_block_ids(), *get_webhook_block_ids()]
),
)
return GraphExecution.from_db(graph_exec)
@@ -1025,18 +985,6 @@ class NodeExecutionEvent(NodeExecutionResult):
)
class SharedExecutionResponse(BaseModel):
"""Public-safe response for shared executions"""
id: str
graph_name: str
graph_description: Optional[str]
status: ExecutionStatus
created_at: datetime
outputs: CompletedBlockOutput # Only the final outputs, no intermediate data
# Deliberately exclude: user_id, inputs, credentials, node details
ExecutionEvent = Annotated[
GraphExecutionEvent | NodeExecutionEvent, Field(discriminator="event_type")
]
@@ -1214,98 +1162,3 @@ async def get_block_error_stats(
)
for row in result
]
async def update_graph_execution_share_status(
execution_id: str,
user_id: str,
is_shared: bool,
share_token: str | None,
shared_at: datetime | None,
) -> None:
"""Update the sharing status of a graph execution."""
await AgentGraphExecution.prisma().update(
where={"id": execution_id},
data={
"isShared": is_shared,
"shareToken": share_token,
"sharedAt": shared_at,
},
)
async def get_graph_execution_by_share_token(
share_token: str,
) -> SharedExecutionResponse | None:
"""Get a shared execution with limited public-safe data."""
execution = await AgentGraphExecution.prisma().find_first(
where={
"shareToken": share_token,
"isShared": True,
"isDeleted": False,
},
include={
"AgentGraph": True,
"NodeExecutions": {
"include": {
"Output": True,
"Node": {
"include": {
"AgentBlock": True,
}
},
},
},
},
)
if not execution:
return None
# Extract outputs from OUTPUT blocks only (consistent with GraphExecution.from_db)
outputs: CompletedBlockOutput = defaultdict(list)
if execution.NodeExecutions:
for node_exec in execution.NodeExecutions:
if node_exec.Node and node_exec.Node.agentBlockId:
# Get the block definition to check its type
block = get_block(node_exec.Node.agentBlockId)
if block and block.block_type == BlockType.OUTPUT:
# For OUTPUT blocks, the data is stored in executionData or Input
# The executionData contains the structured input with 'name' and 'value' fields
if hasattr(node_exec, "executionData") and node_exec.executionData:
exec_data = type_utils.convert(
node_exec.executionData, dict[str, Any]
)
if "name" in exec_data:
name = exec_data["name"]
value = exec_data.get("value")
outputs[name].append(value)
elif node_exec.Input:
# Build input_data from Input relation
input_data = {}
for data in node_exec.Input:
if data.name and data.data is not None:
input_data[data.name] = type_utils.convert(
data.data, JsonValue
)
if "name" in input_data:
name = input_data["name"]
value = input_data.get("value")
outputs[name].append(value)
return SharedExecutionResponse(
id=execution.id,
graph_name=(
execution.AgentGraph.name
if (execution.AgentGraph and execution.AgentGraph.name)
else "Untitled Agent"
),
graph_description=(
execution.AgentGraph.description if execution.AgentGraph else None
),
status=ExecutionStatus(execution.executionStatus),
created_at=execution.createdAt,
outputs=outputs,
)

View File

@@ -1,7 +1,6 @@
import logging
import uuid
from collections import defaultdict
from datetime import datetime, timezone
from typing import TYPE_CHECKING, Any, Literal, Optional, cast
from prisma.enums import SubmissionStatus
@@ -29,7 +28,6 @@ from backend.data.model import (
from backend.integrations.providers import ProviderName
from backend.util import type as type_utils
from backend.util.json import SafeJson
from backend.util.models import Pagination
from .block import Block, BlockInput, BlockSchema, BlockType, get_block, get_blocks
from .db import BaseDbModel, query_raw_with_schema, transaction
@@ -162,7 +160,6 @@ class BaseGraph(BaseDbModel):
is_active: bool = True
name: str
description: str
instructions: str | None = None
recommended_schedule_cron: str | None = None
nodes: list[Node] = []
links: list[Link] = []
@@ -384,8 +381,6 @@ class GraphModel(Graph):
user_id: str
nodes: list[NodeModel] = [] # type: ignore
created_at: datetime
@property
def starting_nodes(self) -> list[NodeModel]:
outbound_nodes = {link.sink_id for link in self.links}
@@ -398,10 +393,6 @@ class GraphModel(Graph):
if node.id not in outbound_nodes or node.id in input_nodes
]
@property
def webhook_input_node(self) -> NodeModel | None: # type: ignore
return cast(NodeModel, super().webhook_input_node)
def meta(self) -> "GraphMeta":
"""
Returns a GraphMeta object with metadata about the graph.
@@ -703,11 +694,9 @@ class GraphModel(Graph):
version=graph.version,
forked_from_id=graph.forkedFromId,
forked_from_version=graph.forkedFromVersion,
created_at=graph.createdAt,
is_active=graph.isActive,
name=graph.name or "",
description=graph.description or "",
instructions=graph.instructions,
recommended_schedule_cron=graph.recommendedScheduleCron,
nodes=[NodeModel.from_db(node, for_export) for node in graph.Nodes or []],
links=list(
@@ -747,13 +736,6 @@ class GraphMeta(Graph):
return GraphMeta(**graph.model_dump())
class GraphsPaginated(BaseModel):
"""Response schema for paginated graphs."""
graphs: list[GraphMeta]
pagination: Pagination
# --------------------- CRUD functions --------------------- #
@@ -782,42 +764,31 @@ async def set_node_webhook(node_id: str, webhook_id: str | None) -> NodeModel:
return NodeModel.from_db(node)
async def list_graphs_paginated(
async def list_graphs(
user_id: str,
page: int = 1,
page_size: int = 25,
filter_by: Literal["active"] | None = "active",
) -> GraphsPaginated:
) -> list[GraphMeta]:
"""
Retrieves paginated graph metadata objects.
Retrieves graph metadata objects.
Default behaviour is to get all currently active graphs.
Args:
user_id: The ID of the user that owns the graphs.
page: Page number (1-based).
page_size: Number of graphs per page.
filter_by: An optional filter to either select graphs.
user_id: The ID of the user that owns the graph.
Returns:
GraphsPaginated: Paginated list of graph metadata.
list[GraphMeta]: A list of objects representing the retrieved graphs.
"""
where_clause: AgentGraphWhereInput = {"userId": user_id}
if filter_by == "active":
where_clause["isActive"] = True
# Get total count
total_count = await AgentGraph.prisma().count(where=where_clause)
total_pages = (total_count + page_size - 1) // page_size
# Get paginated results
offset = (page - 1) * page_size
graphs = await AgentGraph.prisma().find_many(
where=where_clause,
distinct=["id"],
order={"version": "desc"},
include=AGENT_GRAPH_INCLUDE,
skip=offset,
take=page_size,
)
graph_models: list[GraphMeta] = []
@@ -831,15 +802,7 @@ async def list_graphs_paginated(
logger.error(f"Error processing graph {graph.id}: {e}")
continue
return GraphsPaginated(
graphs=graph_models,
pagination=Pagination(
total_items=total_count,
total_pages=total_pages,
current_page=page,
page_size=page_size,
),
)
return graph_models
async def get_graph_metadata(graph_id: str, version: int | None = None) -> Graph | None:
@@ -1181,7 +1144,6 @@ def make_graph_model(creatable_graph: Graph, user_id: str) -> GraphModel:
return GraphModel(
**creatable_graph.model_dump(exclude={"nodes"}),
user_id=user_id,
created_at=datetime.now(tz=timezone.utc),
nodes=[
NodeModel(
**creatable_node.model_dump(),

View File

@@ -1,7 +1,8 @@
import logging
import os
from functools import cache
from autogpt_libs.utils.cache import cached, thread_cached
from autogpt_libs.utils.cache import thread_cached
from dotenv import load_dotenv
from redis import Redis
from redis.asyncio import Redis as AsyncRedis
@@ -12,7 +13,7 @@ load_dotenv()
HOST = os.getenv("REDIS_HOST", "localhost")
PORT = int(os.getenv("REDIS_PORT", "6379"))
PASSWORD = os.getenv("REDIS_PASSWORD", None)
PASSWORD = os.getenv("REDIS_PASSWORD", "password")
logger = logging.getLogger(__name__)
@@ -34,7 +35,7 @@ def disconnect():
get_redis().close()
@cached()
@cache
def get_redis() -> Redis:
return connect()

View File

@@ -7,7 +7,6 @@ from typing import Optional, cast
from urllib.parse import quote_plus
from autogpt_libs.auth.models import DEFAULT_USER_ID
from autogpt_libs.utils.cache import cached
from fastapi import HTTPException
from prisma.enums import NotificationType
from prisma.models import User as PrismaUser
@@ -24,11 +23,7 @@ from backend.util.settings import Settings
logger = logging.getLogger(__name__)
settings = Settings()
# Cache decorator alias for consistent user lookup caching
cache_user_lookup = cached(maxsize=1000, ttl_seconds=300)
@cache_user_lookup
async def get_or_create_user(user_data: dict) -> User:
try:
user_id = user_data.get("sub")
@@ -54,7 +49,6 @@ async def get_or_create_user(user_data: dict) -> User:
raise DatabaseError(f"Failed to get or create user {user_data}: {e}") from e
@cache_user_lookup
async def get_user_by_id(user_id: str) -> User:
user = await prisma.user.find_unique(where={"id": user_id})
if not user:
@@ -70,7 +64,6 @@ async def get_user_email_by_id(user_id: str) -> Optional[str]:
raise DatabaseError(f"Failed to get user email for user {user_id}: {e}") from e
@cache_user_lookup
async def get_user_by_email(email: str) -> Optional[User]:
try:
user = await prisma.user.find_unique(where={"email": email})
@@ -81,17 +74,7 @@ async def get_user_by_email(email: str) -> Optional[User]:
async def update_user_email(user_id: str, email: str):
try:
# Get old email first for cache invalidation
old_user = await prisma.user.find_unique(where={"id": user_id})
old_email = old_user.email if old_user else None
await prisma.user.update(where={"id": user_id}, data={"email": email})
# Selectively invalidate only the specific user entries
get_user_by_id.cache_delete(user_id)
if old_email:
get_user_by_email.cache_delete(old_email)
get_user_by_email.cache_delete(email)
except Exception as e:
raise DatabaseError(
f"Failed to update user email for user {user_id}: {e}"
@@ -131,8 +114,6 @@ async def update_user_integrations(user_id: str, data: UserIntegrations):
where={"id": user_id},
data={"integrations": encrypted_data},
)
# Invalidate cache for this user
get_user_by_id.cache_delete(user_id)
async def migrate_and_encrypt_user_integrations():
@@ -304,10 +285,6 @@ async def update_user_notification_preference(
)
if not user:
raise ValueError(f"User not found with ID: {user_id}")
# Invalidate cache for this user since notification preferences are part of user data
get_user_by_id.cache_delete(user_id)
preferences: dict[NotificationType, bool] = {
NotificationType.AGENT_RUN: user.notifyOnAgentRun or True,
NotificationType.ZERO_BALANCE: user.notifyOnZeroBalance or True,
@@ -346,8 +323,6 @@ async def set_user_email_verification(user_id: str, verified: bool) -> None:
where={"id": user_id},
data={"emailVerified": verified},
)
# Invalidate cache for this user
get_user_by_id.cache_delete(user_id)
except Exception as e:
raise DatabaseError(
f"Failed to set email verification status for user {user_id}: {e}"
@@ -432,10 +407,6 @@ async def update_user_timezone(user_id: str, timezone: str) -> User:
)
if not user:
raise ValueError(f"User not found with ID: {user_id}")
# Invalidate cache for this user
get_user_by_id.cache_delete(user_id)
return User.from_db(user)
except Exception as e:
raise DatabaseError(f"Failed to update timezone for user {user_id}: {e}") from e

View File

@@ -107,7 +107,7 @@ async def generate_activity_status_for_execution(
# Check if we have OpenAI API key
try:
settings = Settings()
if not settings.secrets.openai_internal_api_key:
if not settings.secrets.openai_api_key:
logger.debug(
"OpenAI API key not configured, skipping activity status generation"
)
@@ -187,7 +187,7 @@ async def generate_activity_status_for_execution(
credentials = APIKeyCredentials(
id="openai",
provider="openai",
api_key=SecretStr(settings.secrets.openai_internal_api_key),
api_key=SecretStr(settings.secrets.openai_api_key),
title="System OpenAI",
)
@@ -423,6 +423,7 @@ async def _call_llm_direct(
credentials=credentials,
llm_model=LlmModel.GPT4O_MINI,
prompt=prompt,
json_format=False,
max_tokens=150,
compress_prompt_to_fit=True,
)

View File

@@ -468,7 +468,7 @@ class TestGenerateActivityStatusForExecution:
):
mock_get_block.side_effect = lambda block_id: mock_blocks.get(block_id)
mock_settings.return_value.secrets.openai_internal_api_key = "test_key"
mock_settings.return_value.secrets.openai_api_key = "test_key"
mock_llm.return_value = (
"I analyzed your data and provided the requested insights."
)
@@ -520,7 +520,7 @@ class TestGenerateActivityStatusForExecution:
"backend.executor.activity_status_generator.is_feature_enabled",
return_value=True,
):
mock_settings.return_value.secrets.openai_internal_api_key = ""
mock_settings.return_value.secrets.openai_api_key = ""
result = await generate_activity_status_for_execution(
graph_exec_id="test_exec",
@@ -546,7 +546,7 @@ class TestGenerateActivityStatusForExecution:
"backend.executor.activity_status_generator.is_feature_enabled",
return_value=True,
):
mock_settings.return_value.secrets.openai_internal_api_key = "test_key"
mock_settings.return_value.secrets.openai_api_key = "test_key"
result = await generate_activity_status_for_execution(
graph_exec_id="test_exec",
@@ -581,7 +581,7 @@ class TestGenerateActivityStatusForExecution:
):
mock_get_block.side_effect = lambda block_id: mock_blocks.get(block_id)
mock_settings.return_value.secrets.openai_internal_api_key = "test_key"
mock_settings.return_value.secrets.openai_api_key = "test_key"
mock_llm.return_value = "Agent completed execution."
result = await generate_activity_status_for_execution(
@@ -633,7 +633,7 @@ class TestIntegration:
):
mock_get_block.side_effect = lambda block_id: mock_blocks.get(block_id)
mock_settings.return_value.secrets.openai_internal_api_key = "test_key"
mock_settings.return_value.secrets.openai_api_key = "test_key"
mock_response = LLMResponse(
raw_response={},

View File

@@ -85,16 +85,6 @@ class DatabaseManager(AppService):
async def health_check(self) -> str:
if not db.is_connected():
raise UnhealthyServiceError("Database is not connected")
try:
# Test actual database connectivity by executing a simple query
# This will fail if Prisma query engine is not responding
result = await db.query_raw_with_schema("SELECT 1 as health_check")
if not result or result[0].get("health_check") != 1:
raise UnhealthyServiceError("Database query test failed")
except Exception as e:
raise UnhealthyServiceError(f"Database health check failed: {e}")
return await super().health_check()
@classmethod

View File

@@ -605,7 +605,7 @@ class ExecutionProcessor:
)
return
if exec_meta.status in [ExecutionStatus.QUEUED, ExecutionStatus.INCOMPLETE]:
if exec_meta.status == ExecutionStatus.QUEUED:
log_metadata.info(f"⚙️ Starting graph execution #{graph_exec.graph_exec_id}")
exec_meta.status = ExecutionStatus.RUNNING
send_execution_update(

View File

@@ -191,22 +191,15 @@ class GraphExecutionJobInfo(GraphExecutionJobArgs):
id: str
name: str
next_run_time: str
timezone: str = Field(default="UTC", description="Timezone used for scheduling")
@staticmethod
def from_db(
job_args: GraphExecutionJobArgs, job_obj: JobObj
) -> "GraphExecutionJobInfo":
# Extract timezone from the trigger if it's a CronTrigger
timezone_str = "UTC"
if hasattr(job_obj.trigger, "timezone"):
timezone_str = str(job_obj.trigger.timezone)
return GraphExecutionJobInfo(
id=job_obj.id,
name=job_obj.name,
next_run_time=job_obj.next_run_time.isoformat(),
timezone=timezone_str,
**job_args.model_dump(),
)
@@ -402,7 +395,6 @@ class Scheduler(AppService):
input_data: BlockInput,
input_credentials: dict[str, CredentialsMetaInput],
name: Optional[str] = None,
user_timezone: str | None = None,
) -> GraphExecutionJobInfo:
# Validate the graph before scheduling to prevent runtime failures
# We don't need the return value, just want the validation to run
@@ -416,18 +408,7 @@ class Scheduler(AppService):
)
)
# Use provided timezone or default to UTC
# Note: Timezone should be passed from the client to avoid database lookups
if not user_timezone:
user_timezone = "UTC"
logger.warning(
f"No timezone provided for user {user_id}, using UTC for scheduling. "
f"Client should pass user's timezone for correct scheduling."
)
logger.info(
f"Scheduling job for user {user_id} with timezone {user_timezone} (cron: {cron})"
)
logger.info(f"Scheduling job for user {user_id} in UTC (cron: {cron})")
job_args = GraphExecutionJobArgs(
user_id=user_id,
@@ -441,12 +422,12 @@ class Scheduler(AppService):
execute_graph,
kwargs=job_args.model_dump(),
name=name,
trigger=CronTrigger.from_crontab(cron, timezone=user_timezone),
trigger=CronTrigger.from_crontab(cron, timezone="UTC"),
jobstore=Jobstores.EXECUTION.value,
replace_existing=True,
)
logger.info(
f"Added job {job.id} with cron schedule '{cron}' in timezone {user_timezone}, input data: {input_data}"
f"Added job {job.id} with cron schedule '{cron}' in UTC, input data: {input_data}"
)
return GraphExecutionJobInfo.from_db(job_args, job)

View File

@@ -914,30 +914,29 @@ async def add_graph_execution(
preset_id=preset_id,
)
# Fetch user context for the graph execution
user_context = await get_user_context(user_id)
queue = await get_async_execution_queue()
graph_exec_entry = graph_exec.to_graph_execution_entry(
user_context=await get_user_context(user_id),
compiled_nodes_input_masks=compiled_nodes_input_masks,
user_context, compiled_nodes_input_masks
)
logger.info(
f"Created graph execution #{graph_exec.id} for graph "
f"#{graph_id} with {len(starting_nodes_input)} starting nodes. "
f"Now publishing to execution queue."
)
exec_queue = await get_async_execution_queue()
await exec_queue.publish_message(
await queue.publish_message(
routing_key=GRAPH_EXECUTION_ROUTING_KEY,
message=graph_exec_entry.model_dump_json(),
exchange=GRAPH_EXECUTION_EXCHANGE,
)
logger.info(f"Published execution {graph_exec.id} to RabbitMQ queue")
graph_exec.status = ExecutionStatus.QUEUED
await edb.update_graph_execution_stats(
graph_exec_id=graph_exec.id,
status=graph_exec.status,
)
await get_async_execution_event_bus().publish(graph_exec)
bus = get_async_execution_event_bus()
await bus.publish(graph_exec)
return graph_exec
except BaseException as e:

View File

@@ -316,7 +316,6 @@ async def test_add_graph_execution_is_repeatable(mocker: MockerFixture):
# Mock the graph execution object
mock_graph_exec = mocker.MagicMock(spec=GraphExecutionWithNodes)
mock_graph_exec.id = "execution-id-123"
mock_graph_exec.node_executions = [] # Add this to avoid AttributeError
mock_graph_exec.to_graph_execution_entry.return_value = mocker.MagicMock()
# Mock user context
@@ -347,10 +346,6 @@ async def test_add_graph_execution_is_repeatable(mocker: MockerFixture):
)
mock_prisma.is_connected.return_value = True
mock_edb.create_graph_execution = mocker.AsyncMock(return_value=mock_graph_exec)
mock_edb.update_graph_execution_stats = mocker.AsyncMock(
return_value=mock_graph_exec
)
mock_edb.update_node_execution_status_batch = mocker.AsyncMock()
mock_get_user_context.return_value = mock_user_context
mock_get_queue.return_value = mock_queue
mock_get_event_bus.return_value = mock_event_bus

View File

@@ -1,14 +1,13 @@
import functools
from typing import TYPE_CHECKING
from autogpt_libs.utils.cache import cached
if TYPE_CHECKING:
from ..providers import ProviderName
from ._base import BaseWebhooksManager
# --8<-- [start:load_webhook_managers]
@cached()
@functools.cache
def load_webhook_managers() -> dict["ProviderName", type["BaseWebhooksManager"]]:
webhook_managers = {}

View File

@@ -7,9 +7,10 @@ from backend.data.graph import set_node_webhook
from backend.integrations.creds_manager import IntegrationCredentialsManager
from . import get_webhook_manager, supports_webhooks
from .utils import setup_webhook_for_block
if TYPE_CHECKING:
from backend.data.graph import BaseGraph, GraphModel, NodeModel
from backend.data.graph import BaseGraph, GraphModel, Node, NodeModel
from backend.data.model import Credentials
from ._base import BaseWebhooksManager
@@ -42,19 +43,32 @@ async def _on_graph_activate(graph: "BaseGraph", user_id: str) -> "BaseGraph": .
async def _on_graph_activate(graph: "BaseGraph | GraphModel", user_id: str):
get_credentials = credentials_manager.cached_getter(user_id)
updated_nodes = []
for new_node in graph.nodes:
block_input_schema = cast(BlockSchema, new_node.block.input_schema)
for creds_field_name in block_input_schema.get_credentials_fields().keys():
# Prevent saving graph with non-existent credentials
if (
creds_meta := new_node.input_default.get(creds_field_name)
) and not await get_credentials(creds_meta["id"]):
raise ValueError(
f"Node #{new_node.id} input '{creds_field_name}' updated with "
f"non-existent credentials #{creds_meta['id']}"
node_credentials = None
if (
# Webhook-triggered blocks are only allowed to have 1 credentials input
(
creds_field_name := next(
iter(block_input_schema.get_credentials_fields()), None
)
)
and (creds_meta := new_node.input_default.get(creds_field_name))
and not (node_credentials := await get_credentials(creds_meta["id"]))
):
raise ValueError(
f"Node #{new_node.id} input '{creds_field_name}' updated with "
f"non-existent credentials #{creds_meta['id']}"
)
updated_node = await on_node_activate(
user_id, graph.id, new_node, credentials=node_credentials
)
updated_nodes.append(updated_node)
graph.nodes = updated_nodes
return graph
@@ -71,14 +85,20 @@ async def on_graph_deactivate(graph: "GraphModel", user_id: str):
block_input_schema = cast(BlockSchema, node.block.input_schema)
node_credentials = None
for creds_field_name in block_input_schema.get_credentials_fields().keys():
if (creds_meta := node.input_default.get(creds_field_name)) and not (
node_credentials := await get_credentials(creds_meta["id"])
):
logger.warning(
f"Node #{node.id} input '{creds_field_name}' referenced "
f"non-existent credentials #{creds_meta['id']}"
if (
# Webhook-triggered blocks are only allowed to have 1 credentials input
(
creds_field_name := next(
iter(block_input_schema.get_credentials_fields()), None
)
)
and (creds_meta := node.input_default.get(creds_field_name))
and not (node_credentials := await get_credentials(creds_meta["id"]))
):
logger.error(
f"Node #{node.id} input '{creds_field_name}' referenced non-existent "
f"credentials #{creds_meta['id']}"
)
updated_node = await on_node_deactivate(
user_id, node, credentials=node_credentials
@@ -89,6 +109,32 @@ async def on_graph_deactivate(graph: "GraphModel", user_id: str):
return graph
async def on_node_activate(
user_id: str,
graph_id: str,
node: "Node",
*,
credentials: Optional["Credentials"] = None,
) -> "Node":
"""Hook to be called when the node is activated/created"""
if node.block.webhook_config:
new_webhook, feedback = await setup_webhook_for_block(
user_id=user_id,
trigger_block=node.block,
trigger_config=node.input_default,
for_graph_id=graph_id,
)
if new_webhook:
node = await set_node_webhook(node.id, new_webhook.id)
else:
logger.debug(
f"Node #{node.id} does not have everything for a webhook: {feedback}"
)
return node
async def on_node_deactivate(
user_id: str,
node: "NodeModel",

View File

@@ -4,6 +4,7 @@ from typing import TYPE_CHECKING, Optional, cast
from pydantic import JsonValue
from backend.integrations.creds_manager import IntegrationCredentialsManager
from backend.integrations.providers import ProviderName
from backend.util.settings import Config
from . import get_webhook_manager, supports_webhooks
@@ -12,7 +13,6 @@ if TYPE_CHECKING:
from backend.data.block import Block, BlockSchema
from backend.data.integrations import Webhook
from backend.data.model import Credentials
from backend.integrations.providers import ProviderName
logger = logging.getLogger(__name__)
app_config = Config()
@@ -20,7 +20,7 @@ credentials_manager = IntegrationCredentialsManager()
# TODO: add test to assert this matches the actual API route
def webhook_ingress_url(provider_name: "ProviderName", webhook_id: str) -> str:
def webhook_ingress_url(provider_name: ProviderName, webhook_id: str) -> str:
return (
f"{app_config.platform_base_url}/api/integrations/{provider_name.value}"
f"/webhooks/{webhook_id}/ingress"
@@ -144,69 +144,3 @@ async def setup_webhook_for_block(
)
logger.debug(f"Acquired webhook: {webhook}")
return webhook, None
async def migrate_legacy_triggered_graphs():
from prisma.models import AgentGraph
from backend.data.graph import AGENT_GRAPH_INCLUDE, GraphModel, set_node_webhook
from backend.data.model import is_credentials_field_name
from backend.server.v2.library.db import create_preset
from backend.server.v2.library.model import LibraryAgentPresetCreatable
triggered_graphs = [
GraphModel.from_db(_graph)
for _graph in await AgentGraph.prisma().find_many(
where={
"isActive": True,
"Nodes": {"some": {"NOT": [{"webhookId": None}]}},
},
include=AGENT_GRAPH_INCLUDE,
)
]
n_migrated_webhooks = 0
for graph in triggered_graphs:
try:
if not (
(trigger_node := graph.webhook_input_node) and trigger_node.webhook_id
):
continue
# Use trigger node's inputs for the preset
preset_credentials = {
field_name: creds_meta
for field_name, creds_meta in trigger_node.input_default.items()
if is_credentials_field_name(field_name)
}
preset_inputs = {
field_name: value
for field_name, value in trigger_node.input_default.items()
if not is_credentials_field_name(field_name)
}
# Create a triggered preset for the graph
await create_preset(
graph.user_id,
LibraryAgentPresetCreatable(
graph_id=graph.id,
graph_version=graph.version,
inputs=preset_inputs,
credentials=preset_credentials,
name=graph.name,
description=graph.description,
webhook_id=trigger_node.webhook_id,
is_active=True,
),
)
# Detach webhook from the graph node
await set_node_webhook(trigger_node.id, None)
n_migrated_webhooks += 1
except Exception as e:
logger.error(f"Failed to migrate graph #{graph.id} trigger to preset: {e}")
continue
logger.info(f"Migrated {n_migrated_webhooks} node triggers to triggered presets")

View File

@@ -1,287 +0,0 @@
"""
Prometheus instrumentation for FastAPI services.
This module provides centralized metrics collection and instrumentation
for all FastAPI services in the AutoGPT platform.
"""
import logging
from typing import Optional
from fastapi import FastAPI
from prometheus_client import Counter, Gauge, Histogram, Info
from prometheus_fastapi_instrumentator import Instrumentator, metrics
logger = logging.getLogger(__name__)
# Custom business metrics with controlled cardinality
GRAPH_EXECUTIONS = Counter(
"autogpt_graph_executions_total",
"Total number of graph executions",
labelnames=[
"status"
], # Removed graph_id and user_id to prevent cardinality explosion
)
GRAPH_EXECUTIONS_BY_USER = Counter(
"autogpt_graph_executions_by_user_total",
"Total number of graph executions by user (sampled)",
labelnames=["status"], # Only status, user_id tracked separately when needed
)
BLOCK_EXECUTIONS = Counter(
"autogpt_block_executions_total",
"Total number of block executions",
labelnames=["block_type", "status"], # block_type is bounded
)
BLOCK_DURATION = Histogram(
"autogpt_block_duration_seconds",
"Duration of block executions in seconds",
labelnames=["block_type"],
buckets=[0.1, 0.25, 0.5, 1, 2.5, 5, 10, 30, 60],
)
WEBSOCKET_CONNECTIONS = Gauge(
"autogpt_websocket_connections_total",
"Total number of active WebSocket connections",
# Removed user_id label - track total only to prevent cardinality explosion
)
SCHEDULER_JOBS = Gauge(
"autogpt_scheduler_jobs",
"Current number of scheduled jobs",
labelnames=["job_type", "status"],
)
DATABASE_QUERIES = Histogram(
"autogpt_database_query_duration_seconds",
"Duration of database queries in seconds",
labelnames=["operation", "table"],
buckets=[0.01, 0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
)
RABBITMQ_MESSAGES = Counter(
"autogpt_rabbitmq_messages_total",
"Total number of RabbitMQ messages",
labelnames=["queue", "status"],
)
AUTHENTICATION_ATTEMPTS = Counter(
"autogpt_auth_attempts_total",
"Total number of authentication attempts",
labelnames=["method", "status"],
)
API_KEY_USAGE = Counter(
"autogpt_api_key_usage_total",
"API key usage by provider",
labelnames=["provider", "block_type", "status"],
)
# Function/operation level metrics with controlled cardinality
GRAPH_OPERATIONS = Counter(
"autogpt_graph_operations_total",
"Graph operations by type",
labelnames=["operation", "status"], # create, update, delete, execute, etc.
)
USER_OPERATIONS = Counter(
"autogpt_user_operations_total",
"User operations by type",
labelnames=["operation", "status"], # login, register, update_profile, etc.
)
RATE_LIMIT_HITS = Counter(
"autogpt_rate_limit_hits_total",
"Number of rate limit hits",
labelnames=["endpoint"], # Removed user_id to prevent cardinality explosion
)
SERVICE_INFO = Info(
"autogpt_service",
"Service information",
)
def instrument_fastapi(
app: FastAPI,
service_name: str,
expose_endpoint: bool = True,
endpoint: str = "/metrics",
include_in_schema: bool = False,
excluded_handlers: Optional[list] = None,
) -> Instrumentator:
"""
Instrument a FastAPI application with Prometheus metrics.
Args:
app: FastAPI application instance
service_name: Name of the service for metrics labeling
expose_endpoint: Whether to expose /metrics endpoint
endpoint: Path for metrics endpoint
include_in_schema: Whether to include metrics endpoint in OpenAPI schema
excluded_handlers: List of paths to exclude from metrics
Returns:
Configured Instrumentator instance
"""
# Set service info
try:
from importlib.metadata import version
service_version = version("autogpt-platform-backend")
except Exception:
service_version = "unknown"
SERVICE_INFO.info(
{
"service": service_name,
"version": service_version,
}
)
# Create instrumentator with default metrics
instrumentator = Instrumentator(
should_group_status_codes=True,
should_ignore_untemplated=True,
should_respect_env_var=True,
should_instrument_requests_inprogress=True,
excluded_handlers=excluded_handlers or ["/health", "/readiness"],
env_var_name="ENABLE_METRICS",
inprogress_name="autogpt_http_requests_inprogress",
inprogress_labels=True,
)
# Add default HTTP metrics
instrumentator.add(
metrics.default(
metric_namespace="autogpt",
metric_subsystem=service_name.replace("-", "_"),
)
)
# Add request size metrics
instrumentator.add(
metrics.request_size(
metric_namespace="autogpt",
metric_subsystem=service_name.replace("-", "_"),
)
)
# Add response size metrics
instrumentator.add(
metrics.response_size(
metric_namespace="autogpt",
metric_subsystem=service_name.replace("-", "_"),
)
)
# Add latency metrics with custom buckets for better granularity
instrumentator.add(
metrics.latency(
metric_namespace="autogpt",
metric_subsystem=service_name.replace("-", "_"),
buckets=[0.01, 0.025, 0.05, 0.1, 0.25, 0.5, 1, 2.5, 5, 10, 30, 60],
)
)
# Add combined metrics (requests by method and status)
instrumentator.add(
metrics.combined_size(
metric_namespace="autogpt",
metric_subsystem=service_name.replace("-", "_"),
)
)
# Instrument the app
instrumentator.instrument(app)
# Expose metrics endpoint if requested
if expose_endpoint:
instrumentator.expose(
app,
endpoint=endpoint,
include_in_schema=include_in_schema,
tags=["monitoring"] if include_in_schema else None,
)
logger.info(f"Metrics endpoint exposed at {endpoint} for {service_name}")
return instrumentator
def record_graph_execution(graph_id: str, status: str, user_id: str):
"""Record a graph execution event.
Args:
graph_id: Graph identifier (kept for future sampling/debugging)
status: Execution status (success/error/validation_error)
user_id: User identifier (kept for future sampling/debugging)
"""
# Track overall executions without high-cardinality labels
GRAPH_EXECUTIONS.labels(status=status).inc()
# Optionally track per-user executions (implement sampling if needed)
# For now, just track status to avoid cardinality explosion
GRAPH_EXECUTIONS_BY_USER.labels(status=status).inc()
def record_block_execution(block_type: str, status: str, duration: float):
"""Record a block execution event with duration."""
BLOCK_EXECUTIONS.labels(block_type=block_type, status=status).inc()
BLOCK_DURATION.labels(block_type=block_type).observe(duration)
def update_websocket_connections(user_id: str, delta: int):
"""Update the number of active WebSocket connections.
Args:
user_id: User identifier (kept for future sampling/debugging)
delta: Change in connection count (+1 for connect, -1 for disconnect)
"""
# Track total connections without user_id to prevent cardinality explosion
if delta > 0:
WEBSOCKET_CONNECTIONS.inc(delta)
else:
WEBSOCKET_CONNECTIONS.dec(abs(delta))
def record_database_query(operation: str, table: str, duration: float):
"""Record a database query with duration."""
DATABASE_QUERIES.labels(operation=operation, table=table).observe(duration)
def record_rabbitmq_message(queue: str, status: str):
"""Record a RabbitMQ message event."""
RABBITMQ_MESSAGES.labels(queue=queue, status=status).inc()
def record_authentication_attempt(method: str, status: str):
"""Record an authentication attempt."""
AUTHENTICATION_ATTEMPTS.labels(method=method, status=status).inc()
def record_api_key_usage(provider: str, block_type: str, status: str):
"""Record API key usage by provider and block."""
API_KEY_USAGE.labels(provider=provider, block_type=block_type, status=status).inc()
def record_rate_limit_hit(endpoint: str, user_id: str):
"""Record a rate limit hit.
Args:
endpoint: API endpoint that was rate limited
user_id: User identifier (kept for future sampling/debugging)
"""
RATE_LIMIT_HITS.labels(endpoint=endpoint).inc()
def record_graph_operation(operation: str, status: str):
"""Record a graph operation (create, update, delete, execute, etc.)."""
GRAPH_OPERATIONS.labels(operation=operation, status=status).inc()
def record_user_operation(operation: str, status: str):
"""Record a user operation (login, register, etc.)."""
USER_OPERATIONS.labels(operation=operation, status=status).inc()

View File

@@ -6,10 +6,10 @@ import logging
import threading
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Type
from pydantic import BaseModel
from pydantic import BaseModel, SecretStr
from backend.blocks.basic import Block
from backend.data.model import Credentials
from backend.data.model import APIKeyCredentials, Credentials
from backend.integrations.oauth.base import BaseOAuthHandler
from backend.integrations.providers import ProviderName
from backend.integrations.webhooks._base import BaseWebhooksManager
@@ -17,8 +17,6 @@ from backend.integrations.webhooks._base import BaseWebhooksManager
if TYPE_CHECKING:
from backend.sdk.provider import Provider
logger = logging.getLogger(__name__)
class SDKOAuthCredentials(BaseModel):
"""OAuth credentials configuration for SDK providers."""
@@ -104,8 +102,21 @@ class AutoRegistry:
"""Register an environment variable as an API key for a provider."""
with cls._lock:
cls._api_key_mappings[provider] = env_var_name
# Note: The credential itself is created by ProviderBuilder.with_api_key()
# We only store the mapping here to avoid duplication
# Dynamically check if the env var exists and create credential
import os
api_key = os.getenv(env_var_name)
if api_key:
credential = APIKeyCredentials(
id=f"{provider}-default",
provider=provider,
api_key=SecretStr(api_key),
title=f"Default {provider} credentials",
)
# Check if credential already exists to avoid duplicates
if not any(c.id == credential.id for c in cls._default_credentials):
cls._default_credentials.append(credential)
@classmethod
def get_all_credentials(cls) -> List[Credentials]:
@@ -199,43 +210,3 @@ class AutoRegistry:
webhooks.load_webhook_managers = patched_load
except Exception as e:
logging.warning(f"Failed to patch webhook managers: {e}")
# Patch credentials store to include SDK-registered credentials
try:
import sys
from typing import Any
# Get the module from sys.modules to respect mocking
if "backend.integrations.credentials_store" in sys.modules:
creds_store: Any = sys.modules["backend.integrations.credentials_store"]
else:
import backend.integrations.credentials_store
creds_store: Any = backend.integrations.credentials_store
if hasattr(creds_store, "IntegrationCredentialsStore"):
store_class = creds_store.IntegrationCredentialsStore
if hasattr(store_class, "get_all_creds"):
original_get_all_creds = store_class.get_all_creds
async def patched_get_all_creds(self, user_id: str):
# Get original credentials
original_creds = await original_get_all_creds(self, user_id)
# Add SDK-registered credentials
sdk_creds = cls.get_all_credentials()
# Combine credentials, avoiding duplicates by ID
existing_ids = {c.id for c in original_creds}
for cred in sdk_creds:
if cred.id not in existing_ids:
original_creds.append(cred)
return original_creds
store_class.get_all_creds = patched_get_all_creds
logger.info(
"Successfully patched IntegrationCredentialsStore.get_all_creds"
)
except Exception as e:
logging.warning(f"Failed to patch credentials store: {e}")

View File

@@ -1,6 +1,5 @@
from fastapi import FastAPI
from backend.monitoring.instrumentation import instrument_fastapi
from backend.server.middleware.security import SecurityHeadersMiddleware
from .routes.v1 import v1_router
@@ -14,12 +13,3 @@ external_app = FastAPI(
external_app.add_middleware(SecurityHeadersMiddleware)
external_app.include_router(v1_router, prefix="/v1")
# Add Prometheus instrumentation
instrument_fastapi(
external_app,
service_name="external-api",
expose_endpoint=True,
endpoint="/metrics",
include_in_schema=True,
)

View File

@@ -49,7 +49,7 @@ class GraphExecutionResult(TypedDict):
tags=["blocks"],
dependencies=[Security(require_permission(APIKeyPermission.READ_BLOCK))],
)
async def get_graph_blocks() -> Sequence[dict[Any, Any]]:
def get_graph_blocks() -> Sequence[dict[Any, Any]]:
blocks = [block() for block in backend.data.block.get_blocks().values()]
return [b.to_dict() for b in blocks if not b.disabled]

View File

@@ -81,10 +81,6 @@ class SecurityHeadersMiddleware(BaseHTTPMiddleware):
response.headers["X-XSS-Protection"] = "1; mode=block"
response.headers["Referrer-Policy"] = "strict-origin-when-cross-origin"
# Add noindex header for shared execution pages
if "/public/shared" in request.url.path:
response.headers["X-Robots-Tag"] = "noindex, nofollow"
# Default: Disable caching for all endpoints
# Only allow caching for explicitly permitted paths
if not self.is_cacheable_path(request.url.path):

View File

@@ -18,7 +18,6 @@ import backend.data.block
import backend.data.db
import backend.data.graph
import backend.data.user
import backend.integrations.webhooks.utils
import backend.server.routers.postmark.postmark
import backend.server.routers.v1
import backend.server.v2.admin.credit_admin_routes
@@ -37,7 +36,6 @@ import backend.util.settings
from backend.blocks.llm import LlmModel
from backend.data.model import Credentials
from backend.integrations.providers import ProviderName
from backend.monitoring.instrumentation import instrument_fastapi
from backend.server.external.api import external_app
from backend.server.middleware.security import SecurityHeadersMiddleware
from backend.util import json
@@ -80,8 +78,6 @@ async def lifespan_context(app: fastapi.FastAPI):
await backend.data.user.migrate_and_encrypt_user_integrations()
await backend.data.graph.fix_llm_provider_credentials()
await backend.data.graph.migrate_llm_models(LlmModel.GPT4O)
await backend.integrations.webhooks.utils.migrate_legacy_triggered_graphs()
with launch_darkly_context():
yield
@@ -143,16 +139,6 @@ app.add_middleware(SecurityHeadersMiddleware)
# Add 401 responses to authenticated endpoints in OpenAPI spec
add_auth_responses_to_openapi(app)
# Add Prometheus instrumentation
instrument_fastapi(
app,
service_name="rest-api",
expose_endpoint=True,
endpoint="/metrics",
include_in_schema=settings.config.app_env
== backend.util.settings.AppEnvironment.LOCAL,
)
def handle_internal_http_error(status_code: int = 500, log_error: bool = True):
def handler(request: fastapi.Request, exc: Exception):
@@ -266,13 +252,19 @@ async def health():
class AgentServer(backend.util.service.AppProcess):
def run(self):
server_app = starlette.middleware.cors.CORSMiddleware(
app=app,
allow_origins=settings.config.backend_cors_allow_origins,
allow_credentials=True,
allow_methods=["*"], # Allows all methods
allow_headers=["*"], # Allows all headers
)
if settings.config.enable_cors_all_origins:
server_app = starlette.middleware.cors.CORSMiddleware(
app=app,
allow_origins=settings.config.backend_cors_allow_origins,
allow_credentials=True,
allow_methods=["*"], # Allows all methods
allow_headers=["*"], # Allows all headers
)
else:
logger.info("CORS is disabled")
server_app = app
uvicorn.run(
server_app,
host=backend.util.settings.Config().agent_api_host,

View File

@@ -1,17 +1,14 @@
import asyncio
import base64
import logging
import time
import uuid
from collections import defaultdict
from datetime import datetime, timezone
from datetime import datetime
from typing import Annotated, Any, Sequence
import pydantic
import stripe
from autogpt_libs.auth import get_user_id, requires_user
from autogpt_libs.auth.jwt_utils import get_jwt_payload
from autogpt_libs.utils.cache import cached
from fastapi import (
APIRouter,
Body,
@@ -39,10 +36,10 @@ from backend.data.credit import (
RefundRequest,
TransactionHistory,
get_auto_top_up,
get_block_costs,
get_user_credit_model,
set_auto_top_up,
)
from backend.data.execution import UserContext
from backend.data.model import CredentialsMetaInput
from backend.data.notifications import NotificationPreference, NotificationPreferenceDTO
from backend.data.onboarding import (
@@ -66,11 +63,6 @@ from backend.integrations.webhooks.graph_lifecycle_hooks import (
on_graph_activate,
on_graph_deactivate,
)
from backend.monitoring.instrumentation import (
record_block_execution,
record_graph_execution,
record_graph_operation,
)
from backend.server.model import (
CreateAPIKeyRequest,
CreateAPIKeyResponse,
@@ -87,6 +79,7 @@ from backend.util.cloud_storage import get_cloud_storage_handler
from backend.util.exceptions import GraphValidationError, NotFoundError
from backend.util.settings import Settings
from backend.util.timezone_utils import (
convert_cron_to_utc,
convert_utc_time_to_user_timezone,
get_user_timezone_or_utc,
)
@@ -104,7 +97,6 @@ def _create_file_size_error(size_bytes: int, max_size_mb: int) -> HTTPException:
settings = Settings()
logger = logging.getLogger(__name__)
_user_credit_model = get_user_credit_model()
# Define the API routes
@@ -263,37 +255,18 @@ async def is_onboarding_enabled():
########################################################
@cached()
def _get_cached_blocks() -> Sequence[dict[Any, Any]]:
"""
Get cached blocks with thundering herd protection.
Uses sync_cache decorator to prevent multiple concurrent requests
from all executing the expensive block loading operation.
"""
from backend.data.credit import get_block_cost
block_classes = get_blocks()
result = []
for block_class in block_classes.values():
block_instance = block_class()
if not block_instance.disabled:
# Get costs for this specific block class without creating another instance
costs = get_block_cost(block_instance)
result.append({**block_instance.to_dict(), "costs": costs})
return result
@v1_router.get(
path="/blocks",
summary="List available blocks",
tags=["blocks"],
dependencies=[Security(requires_user)],
)
async def get_graph_blocks() -> Sequence[dict[Any, Any]]:
return _get_cached_blocks()
def get_graph_blocks() -> Sequence[dict[Any, Any]]:
blocks = [block() for block in get_blocks().values()]
costs = get_block_costs()
return [
{**b.to_dict(), "costs": costs.get(b.id, [])} for b in blocks if not b.disabled
]
@v1_router.post(
@@ -302,45 +275,15 @@ async def get_graph_blocks() -> Sequence[dict[Any, Any]]:
tags=["blocks"],
dependencies=[Security(requires_user)],
)
async def execute_graph_block(
block_id: str, data: BlockInput, user_id: Annotated[str, Security(get_user_id)]
) -> CompletedBlockOutput:
async def execute_graph_block(block_id: str, data: BlockInput) -> CompletedBlockOutput:
obj = get_block(block_id)
if not obj:
raise HTTPException(status_code=404, detail=f"Block #{block_id} not found.")
# Get user context for block execution
user = await get_user_by_id(user_id)
if not user:
raise HTTPException(status_code=404, detail="User not found.")
user_context = UserContext(timezone=user.timezone)
start_time = time.time()
try:
output = defaultdict(list)
async for name, data in obj.execute(
data,
user_context=user_context,
user_id=user_id,
# Note: graph_exec_id and graph_id are not available for direct block execution
):
output[name].append(data)
# Record successful block execution with duration
duration = time.time() - start_time
block_type = obj.__class__.__name__
record_block_execution(
block_type=block_type, status="success", duration=duration
)
return output
except Exception:
# Record failed block execution
duration = time.time() - start_time
block_type = obj.__class__.__name__
record_block_execution(block_type=block_type, status="error", duration=duration)
raise
output = defaultdict(list)
async for name, data in obj.execute(data):
output[name].append(data)
return output
@v1_router.post(
@@ -633,13 +576,7 @@ class DeleteGraphResponse(TypedDict):
async def list_graphs(
user_id: Annotated[str, Security(get_user_id)],
) -> Sequence[graph_db.GraphMeta]:
paginated_result = await graph_db.list_graphs_paginated(
user_id=user_id,
page=1,
page_size=250,
filter_by="active",
)
return paginated_result.graphs
return await graph_db.list_graphs(filter_by="active", user_id=user_id)
@v1_router.get(
@@ -842,7 +779,7 @@ async def execute_graph(
)
try:
result = await execution_utils.add_graph_execution(
return await execution_utils.add_graph_execution(
graph_id=graph_id,
user_id=user_id,
inputs=inputs,
@@ -850,16 +787,7 @@ async def execute_graph(
graph_version=graph_version,
graph_credentials_inputs=credentials_inputs,
)
# Record successful graph execution
record_graph_execution(graph_id=graph_id, status="success", user_id=user_id)
record_graph_operation(operation="execute", status="success")
return result
except GraphValidationError as e:
# Record failed graph execution
record_graph_execution(
graph_id=graph_id, status="validation_error", user_id=user_id
)
record_graph_operation(operation="execute", status="validation_error")
# Return structured validation errors that the frontend can parse
raise HTTPException(
status_code=400,
@@ -870,11 +798,6 @@ async def execute_graph(
"node_errors": e.node_errors,
},
)
except Exception:
# Record any other failures
record_graph_execution(graph_id=graph_id, status="error", user_id=user_id)
record_graph_operation(operation="execute", status="error")
raise
@v1_router.post(
@@ -928,12 +851,7 @@ async def _stop_graph_run(
async def list_graphs_executions(
user_id: Annotated[str, Security(get_user_id)],
) -> list[execution_db.GraphExecutionMeta]:
paginated_result = await execution_db.get_graph_executions_paginated(
user_id=user_id,
page=1,
page_size=250,
)
return paginated_result.executions
return await execution_db.get_graph_executions(user_id=user_id)
@v1_router.get(
@@ -1004,99 +922,6 @@ async def delete_graph_execution(
)
class ShareRequest(pydantic.BaseModel):
"""Optional request body for share endpoint."""
pass # Empty body is fine
class ShareResponse(pydantic.BaseModel):
"""Response from share endpoints."""
share_url: str
share_token: str
@v1_router.post(
"/graphs/{graph_id}/executions/{graph_exec_id}/share",
dependencies=[Security(requires_user)],
)
async def enable_execution_sharing(
graph_id: Annotated[str, Path],
graph_exec_id: Annotated[str, Path],
user_id: Annotated[str, Security(get_user_id)],
_body: ShareRequest = Body(default=ShareRequest()),
) -> ShareResponse:
"""Enable sharing for a graph execution."""
# Verify the execution belongs to the user
execution = await execution_db.get_graph_execution(
user_id=user_id, execution_id=graph_exec_id
)
if not execution:
raise HTTPException(status_code=404, detail="Execution not found")
# Generate a unique share token
share_token = str(uuid.uuid4())
# Update the execution with share info
await execution_db.update_graph_execution_share_status(
execution_id=graph_exec_id,
user_id=user_id,
is_shared=True,
share_token=share_token,
shared_at=datetime.now(timezone.utc),
)
# Return the share URL
frontend_url = Settings().config.frontend_base_url or "http://localhost:3000"
share_url = f"{frontend_url}/share/{share_token}"
return ShareResponse(share_url=share_url, share_token=share_token)
@v1_router.delete(
"/graphs/{graph_id}/executions/{graph_exec_id}/share",
status_code=HTTP_204_NO_CONTENT,
dependencies=[Security(requires_user)],
)
async def disable_execution_sharing(
graph_id: Annotated[str, Path],
graph_exec_id: Annotated[str, Path],
user_id: Annotated[str, Security(get_user_id)],
) -> None:
"""Disable sharing for a graph execution."""
# Verify the execution belongs to the user
execution = await execution_db.get_graph_execution(
user_id=user_id, execution_id=graph_exec_id
)
if not execution:
raise HTTPException(status_code=404, detail="Execution not found")
# Remove share info
await execution_db.update_graph_execution_share_status(
execution_id=graph_exec_id,
user_id=user_id,
is_shared=False,
share_token=None,
shared_at=None,
)
@v1_router.get("/public/shared/{share_token}")
async def get_shared_execution(
share_token: Annotated[
str,
Path(regex=r"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$"),
],
) -> execution_db.SharedExecutionResponse:
"""Get a shared graph execution by share token (no auth required)."""
execution = await execution_db.get_graph_execution_by_share_token(share_token)
if not execution:
raise HTTPException(status_code=404, detail="Shared execution not found")
return execution
########################################################
##################### Schedules ########################
########################################################
@@ -1108,10 +933,6 @@ class ScheduleCreationRequest(pydantic.BaseModel):
cron: str
inputs: dict[str, Any]
credentials: dict[str, CredentialsMetaInput] = pydantic.Field(default_factory=dict)
timezone: Optional[str] = pydantic.Field(
default=None,
description="User's timezone for scheduling (e.g., 'America/New_York'). If not provided, will use user's saved timezone or UTC.",
)
@v1_router.post(
@@ -1136,22 +957,26 @@ async def create_graph_execution_schedule(
detail=f"Graph #{graph_id} v{schedule_params.graph_version} not found.",
)
# Use timezone from request if provided, otherwise fetch from user profile
if schedule_params.timezone:
user_timezone = schedule_params.timezone
else:
user = await get_user_by_id(user_id)
user_timezone = get_user_timezone_or_utc(user.timezone if user else None)
user = await get_user_by_id(user_id)
user_timezone = get_user_timezone_or_utc(user.timezone if user else None)
# Convert cron expression from user timezone to UTC
try:
utc_cron = convert_cron_to_utc(schedule_params.cron, user_timezone)
except ValueError as e:
raise HTTPException(
status_code=400,
detail=f"Invalid cron expression for timezone {user_timezone}: {e}",
)
result = await get_scheduler_client().add_execution_schedule(
user_id=user_id,
graph_id=graph_id,
graph_version=graph.version,
name=schedule_params.name,
cron=schedule_params.cron,
cron=utc_cron, # Send UTC cron to scheduler
input_data=schedule_params.inputs,
input_credentials=schedule_params.credentials,
user_timezone=user_timezone,
)
# Convert the next_run_time back to user timezone for display
@@ -1173,11 +998,24 @@ async def list_graph_execution_schedules(
user_id: Annotated[str, Security(get_user_id)],
graph_id: str = Path(),
) -> list[scheduler.GraphExecutionJobInfo]:
return await get_scheduler_client().get_execution_schedules(
schedules = await get_scheduler_client().get_execution_schedules(
user_id=user_id,
graph_id=graph_id,
)
# Get user timezone for conversion
user = await get_user_by_id(user_id)
user_timezone = get_user_timezone_or_utc(user.timezone if user else None)
# Convert next_run_time to user timezone for display
for schedule in schedules:
if schedule.next_run_time:
schedule.next_run_time = convert_utc_time_to_user_timezone(
schedule.next_run_time, user_timezone
)
return schedules
@v1_router.get(
path="/schedules",
@@ -1188,7 +1026,20 @@ async def list_graph_execution_schedules(
async def list_all_graphs_execution_schedules(
user_id: Annotated[str, Security(get_user_id)],
) -> list[scheduler.GraphExecutionJobInfo]:
return await get_scheduler_client().get_execution_schedules(user_id=user_id)
schedules = await get_scheduler_client().get_execution_schedules(user_id=user_id)
# Get user timezone for conversion
user = await get_user_by_id(user_id)
user_timezone = get_user_timezone_or_utc(user.timezone if user else None)
# Convert UTC next_run_time to user timezone for display
for schedule in schedules:
if schedule.next_run_time:
schedule.next_run_time = convert_utc_time_to_user_timezone(
schedule.next_run_time, user_timezone
)
return schedules
@v1_router.delete(

View File

@@ -1,5 +1,4 @@
import json
from datetime import datetime
from io import BytesIO
from unittest.mock import AsyncMock, Mock, patch
@@ -110,8 +109,8 @@ def test_get_graph_blocks(
# Mock block costs
mocker.patch(
"backend.data.credit.get_block_cost",
return_value=[{"cost": 10, "type": "credit"}],
"backend.server.routers.v1.get_block_costs",
return_value={"test-block": [{"cost": 10, "type": "credit"}]},
)
response = client.get("/blocks")
@@ -147,15 +146,6 @@ def test_execute_graph_block(
return_value=mock_block,
)
# Mock user for user_context
mock_user = Mock()
mock_user.timezone = "UTC"
mocker.patch(
"backend.server.routers.v1.get_user_by_id",
return_value=mock_user,
)
request_data = {
"input_name": "test_input",
"input_value": "test_value",
@@ -275,12 +265,11 @@ def test_get_graphs(
name="Test Graph",
description="A test graph",
user_id=test_user_id,
created_at=datetime(2025, 9, 4, 13, 37),
)
mocker.patch(
"backend.data.graph.list_graphs_paginated",
return_value=Mock(graphs=[mock_graph]),
"backend.server.routers.v1.graph_db.list_graphs",
return_value=[mock_graph],
)
response = client.get("/graphs")
@@ -310,7 +299,6 @@ def test_get_graph(
name="Test Graph",
description="A test graph",
user_id=test_user_id,
created_at=datetime(2025, 9, 4, 13, 37),
)
mocker.patch(
@@ -360,7 +348,6 @@ def test_delete_graph(
name="Test Graph",
description="A test graph",
user_id=test_user_id,
created_at=datetime(2025, 9, 4, 13, 37),
)
mocker.patch(

View File

@@ -1,8 +1,8 @@
import functools
import logging
from datetime import datetime, timedelta, timezone
import prisma
from autogpt_libs.utils.cache import cached
import backend.data.block
from backend.blocks import load_all_blocks
@@ -296,7 +296,7 @@ def _matches_llm_model(schema_cls: type[BlockSchema], query: str) -> bool:
return False
@cached()
@functools.cache
def _get_all_providers() -> dict[ProviderName, Provider]:
providers: dict[ProviderName, Provider] = {}

View File

@@ -144,92 +144,6 @@ async def list_library_agents(
raise store_exceptions.DatabaseError("Failed to fetch library agents") from e
async def list_favorite_library_agents(
user_id: str,
page: int = 1,
page_size: int = 50,
) -> library_model.LibraryAgentResponse:
"""
Retrieves a paginated list of favorite LibraryAgent records for a given user.
Args:
user_id: The ID of the user whose favorite LibraryAgents we want to retrieve.
page: Current page (1-indexed).
page_size: Number of items per page.
Returns:
A LibraryAgentResponse containing the list of favorite agents and pagination details.
Raises:
DatabaseError: If there is an issue fetching from Prisma.
"""
logger.debug(
f"Fetching favorite library agents for user_id={user_id}, "
f"page={page}, page_size={page_size}"
)
if page < 1 or page_size < 1:
logger.warning(f"Invalid pagination: page={page}, page_size={page_size}")
raise store_exceptions.DatabaseError("Invalid pagination input")
where_clause: prisma.types.LibraryAgentWhereInput = {
"userId": user_id,
"isDeleted": False,
"isArchived": False,
"isFavorite": True, # Only fetch favorites
}
# Sort favorites by updated date descending
order_by: prisma.types.LibraryAgentOrderByInput = {"updatedAt": "desc"}
try:
library_agents = await prisma.models.LibraryAgent.prisma().find_many(
where=where_clause,
include=library_agent_include(user_id),
order=order_by,
skip=(page - 1) * page_size,
take=page_size,
)
agent_count = await prisma.models.LibraryAgent.prisma().count(
where=where_clause
)
logger.debug(
f"Retrieved {len(library_agents)} favorite library agents for user #{user_id}"
)
# Only pass valid agents to the response
valid_library_agents: list[library_model.LibraryAgent] = []
for agent in library_agents:
try:
library_agent = library_model.LibraryAgent.from_db(agent)
valid_library_agents.append(library_agent)
except Exception as e:
# Skip this agent if there was an error
logger.error(
f"Error parsing LibraryAgent #{agent.id} from DB item: {e}"
)
continue
# Return the response with only valid agents
return library_model.LibraryAgentResponse(
agents=valid_library_agents,
pagination=Pagination(
total_items=agent_count,
total_pages=(agent_count + page_size - 1) // page_size,
current_page=page,
page_size=page_size,
),
)
except prisma.errors.PrismaError as e:
logger.error(f"Database error fetching favorite library agents: {e}")
raise store_exceptions.DatabaseError(
"Failed to fetch favorite library agents"
) from e
async def get_library_agent(id: str, user_id: str) -> library_model.LibraryAgent:
"""
Get a specific agent from the user's library.
@@ -795,7 +709,10 @@ async def create_preset(
)
for name, data in {
**preset.inputs,
**preset.credentials,
**{
key: creds_meta.model_dump(exclude_none=True)
for key, creds_meta in preset.credentials.items()
},
}.items()
]
},

View File

@@ -43,7 +43,6 @@ class LibraryAgent(pydantic.BaseModel):
name: str
description: str
instructions: str | None = None
input_schema: dict[str, Any] # Should be BlockIOObjectSubSchema in frontend
output_schema: dict[str, Any]
@@ -65,9 +64,6 @@ class LibraryAgent(pydantic.BaseModel):
# Indicates if this agent is the latest version
is_latest_version: bool
# Whether the agent is marked as favorite by the user
is_favorite: bool
# Recommended schedule cron (from marketplace agents)
recommended_schedule_cron: str | None = None
@@ -127,7 +123,6 @@ class LibraryAgent(pydantic.BaseModel):
updated_at=updated_at,
name=graph.name,
description=graph.description,
instructions=graph.instructions,
input_schema=graph.input_schema,
output_schema=graph.output_schema,
credentials_input_schema=(
@@ -138,7 +133,6 @@ class LibraryAgent(pydantic.BaseModel):
new_output=new_output,
can_access_graph=can_access_graph,
is_latest_version=is_latest_version,
is_favorite=agent.isFavorite,
recommended_schedule_cron=agent.AgentGraph.recommendedScheduleCron,
)
@@ -263,7 +257,6 @@ class LibraryAgentPreset(LibraryAgentPresetCreatable):
id: str
user_id: str
created_at: datetime.datetime
updated_at: datetime.datetime
webhook: "Webhook | None"
@@ -293,7 +286,6 @@ class LibraryAgentPreset(LibraryAgentPresetCreatable):
return cls(
id=preset.id,
user_id=preset.userId,
created_at=preset.createdAt,
updated_at=preset.updatedAt,
graph_id=preset.agentGraphId,
graph_version=preset.agentGraphVersion,

View File

@@ -79,54 +79,6 @@ async def list_library_agents(
) from e
@router.get(
"/favorites",
summary="List Favorite Library Agents",
responses={
500: {"description": "Server error", "content": {"application/json": {}}},
},
)
async def list_favorite_library_agents(
user_id: str = Security(autogpt_auth_lib.get_user_id),
page: int = Query(
1,
ge=1,
description="Page number to retrieve (must be >= 1)",
),
page_size: int = Query(
15,
ge=1,
description="Number of agents per page (must be >= 1)",
),
) -> library_model.LibraryAgentResponse:
"""
Get all favorite agents in the user's library.
Args:
user_id: ID of the authenticated user.
page: Page number to retrieve.
page_size: Number of agents per page.
Returns:
A LibraryAgentResponse containing favorite agents and pagination metadata.
Raises:
HTTPException: If a server/database error occurs.
"""
try:
return await library_db.list_favorite_library_agents(
user_id=user_id,
page=page,
page_size=page_size,
)
except Exception as e:
logger.error(f"Could not list favorite library agents for user #{user_id}: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(e),
) from e
@router.get("/{library_agent_id}", summary="Get Library Agent")
async def get_library_agent(
library_agent_id: str,

View File

@@ -54,7 +54,6 @@ async def test_get_library_agents_success(
new_output=False,
can_access_graph=True,
is_latest_version=True,
is_favorite=False,
updated_at=datetime.datetime(2023, 1, 1, 0, 0, 0),
),
library_model.LibraryAgent(
@@ -75,7 +74,6 @@ async def test_get_library_agents_success(
new_output=False,
can_access_graph=False,
is_latest_version=True,
is_favorite=False,
updated_at=datetime.datetime(2023, 1, 1, 0, 0, 0),
),
],
@@ -123,76 +121,6 @@ def test_get_library_agents_error(mocker: pytest_mock.MockFixture, test_user_id:
)
@pytest.mark.asyncio
async def test_get_favorite_library_agents_success(
mocker: pytest_mock.MockFixture,
test_user_id: str,
) -> None:
mocked_value = library_model.LibraryAgentResponse(
agents=[
library_model.LibraryAgent(
id="test-agent-1",
graph_id="test-agent-1",
graph_version=1,
name="Favorite Agent 1",
description="Test Favorite Description 1",
image_url=None,
creator_name="Test Creator",
creator_image_url="",
input_schema={"type": "object", "properties": {}},
output_schema={"type": "object", "properties": {}},
credentials_input_schema={"type": "object", "properties": {}},
has_external_trigger=False,
status=library_model.LibraryAgentStatus.COMPLETED,
recommended_schedule_cron=None,
new_output=False,
can_access_graph=True,
is_latest_version=True,
is_favorite=True,
updated_at=datetime.datetime(2023, 1, 1, 0, 0, 0),
),
],
pagination=Pagination(
total_items=1, total_pages=1, current_page=1, page_size=15
),
)
mock_db_call = mocker.patch(
"backend.server.v2.library.db.list_favorite_library_agents"
)
mock_db_call.return_value = mocked_value
response = client.get("/agents/favorites")
assert response.status_code == 200
data = library_model.LibraryAgentResponse.model_validate(response.json())
assert len(data.agents) == 1
assert data.agents[0].is_favorite is True
assert data.agents[0].name == "Favorite Agent 1"
mock_db_call.assert_called_once_with(
user_id=test_user_id,
page=1,
page_size=15,
)
def test_get_favorite_library_agents_error(
mocker: pytest_mock.MockFixture, test_user_id: str
):
mock_db_call = mocker.patch(
"backend.server.v2.library.db.list_favorite_library_agents"
)
mock_db_call.side_effect = Exception("Test error")
response = client.get("/agents/favorites")
assert response.status_code == 500
mock_db_call.assert_called_once_with(
user_id=test_user_id,
page=1,
page_size=15,
)
def test_add_agent_to_library_success(
mocker: pytest_mock.MockFixture, test_user_id: str
):
@@ -213,7 +141,6 @@ def test_add_agent_to_library_success(
new_output=False,
can_access_graph=True,
is_latest_version=True,
is_favorite=False,
updated_at=FIXED_NOW,
)

View File

@@ -183,29 +183,6 @@ async def get_store_agent_details(
store_listing.hasApprovedVersion if store_listing else False
)
if active_version_id:
agent_by_active = await prisma.models.StoreAgent.prisma().find_first(
where={"storeListingVersionId": active_version_id}
)
if agent_by_active:
agent = agent_by_active
elif store_listing:
latest_approved = (
await prisma.models.StoreListingVersion.prisma().find_first(
where={
"storeListingId": store_listing.id,
"submissionStatus": prisma.enums.SubmissionStatus.APPROVED,
},
order=[{"version": "desc"}],
)
)
if latest_approved:
agent_latest = await prisma.models.StoreAgent.prisma().find_first(
where={"storeListingVersionId": latest_approved.id}
)
if agent_latest:
agent = agent_latest
if store_listing and store_listing.ActiveVersion:
recommended_schedule_cron = (
store_listing.ActiveVersion.recommendedScheduleCron
@@ -499,7 +476,6 @@ async def get_store_submissions(
sub_heading=sub.sub_heading,
slug=sub.slug,
description=sub.description,
instructions=getattr(sub, "instructions", None),
image_urls=sub.image_urls or [],
date_submitted=sub.date_submitted or datetime.now(tz=timezone.utc),
status=sub.status,
@@ -591,7 +567,6 @@ async def create_store_submission(
video_url: str | None = None,
image_urls: list[str] = [],
description: str = "",
instructions: str | None = None,
sub_heading: str = "",
categories: list[str] = [],
changes_summary: str | None = "Initial Submission",
@@ -663,7 +638,6 @@ async def create_store_submission(
video_url=video_url,
image_urls=image_urls,
description=description,
instructions=instructions,
sub_heading=sub_heading,
categories=categories,
changes_summary=changes_summary,
@@ -685,7 +659,6 @@ async def create_store_submission(
videoUrl=video_url,
imageUrls=image_urls,
description=description,
instructions=instructions,
categories=categories,
subHeading=sub_heading,
submissionStatus=prisma.enums.SubmissionStatus.PENDING,
@@ -716,7 +689,6 @@ async def create_store_submission(
slug=slug,
sub_heading=sub_heading,
description=description,
instructions=instructions,
image_urls=image_urls,
date_submitted=listing.createdAt,
status=prisma.enums.SubmissionStatus.PENDING,
@@ -749,7 +721,6 @@ async def edit_store_submission(
categories: list[str] = [],
changes_summary: str | None = "Update submission",
recommended_schedule_cron: str | None = None,
instructions: str | None = None,
) -> backend.server.v2.store.model.StoreSubmission:
"""
Edit an existing store listing submission.
@@ -830,7 +801,6 @@ async def edit_store_submission(
categories=categories,
changes_summary=changes_summary,
recommended_schedule_cron=recommended_schedule_cron,
instructions=instructions,
)
# For PENDING submissions, we can update the existing version
@@ -847,7 +817,6 @@ async def edit_store_submission(
subHeading=sub_heading,
changesSummary=changes_summary,
recommendedScheduleCron=recommended_schedule_cron,
instructions=instructions,
),
)
@@ -866,7 +835,6 @@ async def edit_store_submission(
sub_heading=sub_heading,
slug=current_version.StoreListing.slug,
description=description,
instructions=instructions,
image_urls=image_urls,
date_submitted=updated_version.submittedAt or updated_version.createdAt,
status=updated_version.submissionStatus,
@@ -908,7 +876,6 @@ async def create_store_version(
video_url: str | None = None,
image_urls: list[str] = [],
description: str = "",
instructions: str | None = None,
sub_heading: str = "",
categories: list[str] = [],
changes_summary: str | None = "Initial submission",
@@ -977,7 +944,6 @@ async def create_store_version(
videoUrl=video_url,
imageUrls=image_urls,
description=description,
instructions=instructions,
categories=categories,
subHeading=sub_heading,
submissionStatus=prisma.enums.SubmissionStatus.PENDING,
@@ -999,7 +965,6 @@ async def create_store_version(
slug=listing.slug,
sub_heading=sub_heading,
description=description,
instructions=instructions,
image_urls=image_urls,
date_submitted=datetime.now(),
status=prisma.enums.SubmissionStatus.PENDING,
@@ -1176,20 +1141,7 @@ async def get_my_agents(
try:
search_filter: prisma.types.LibraryAgentWhereInput = {
"userId": user_id,
"AgentGraph": {
"is": {
"StoreListings": {
"none": {
"isDeleted": False,
"Versions": {
"some": {
"isAvailable": True,
}
},
}
}
}
},
"AgentGraph": {"is": {"StoreListings": {"none": {"isDeleted": False}}}},
"isArchived": False,
"isDeleted": False,
}
@@ -1427,7 +1379,6 @@ async def review_store_submission(
"name": store_listing_version.name,
"description": store_listing_version.description,
"recommendedScheduleCron": store_listing_version.recommendedScheduleCron,
"instructions": store_listing_version.instructions,
},
)
@@ -1593,7 +1544,6 @@ async def review_store_submission(
else ""
),
description=submission.description,
instructions=submission.instructions,
image_urls=submission.imageUrls or [],
date_submitted=submission.submittedAt or submission.createdAt,
status=submission.submissionStatus,
@@ -1729,7 +1679,6 @@ async def get_admin_listings_with_versions(
sub_heading=version.subHeading,
slug=listing.slug,
description=version.description,
instructions=version.instructions,
image_urls=version.imageUrls or [],
date_submitted=version.submittedAt or version.createdAt,
status=version.submissionStatus,

View File

@@ -86,27 +86,6 @@ async def test_get_store_agent_details(mocker):
is_available=False,
)
# Mock active version agent (what we want to return for active version)
mock_active_agent = prisma.models.StoreAgent(
listing_id="test-id",
storeListingVersionId="active-version-id",
slug="test-agent",
agent_name="Test Agent Active",
agent_video="active_video.mp4",
agent_image=["active_image.jpg"],
featured=False,
creator_username="creator",
creator_avatar="avatar.jpg",
sub_heading="Test heading active",
description="Test description active",
categories=["test"],
runs=15,
rating=4.8,
versions=["1.0", "2.0"],
updated_at=datetime.now(),
is_available=True,
)
# Create a mock StoreListing result
mock_store_listing = mocker.MagicMock()
mock_store_listing.activeVersionId = "active-version-id"
@@ -114,22 +93,9 @@ async def test_get_store_agent_details(mocker):
mock_store_listing.ActiveVersion = mocker.MagicMock()
mock_store_listing.ActiveVersion.recommendedScheduleCron = None
# Mock StoreAgent prisma call - need to handle multiple calls
# Mock StoreAgent prisma call
mock_store_agent = mocker.patch("prisma.models.StoreAgent.prisma")
# Set up side_effect to return different results for different calls
def mock_find_first_side_effect(*args, **kwargs):
where_clause = kwargs.get("where", {})
if "storeListingVersionId" in where_clause:
# Second call for active version
return mock_active_agent
else:
# First call for initial lookup
return mock_agent
mock_store_agent.return_value.find_first = mocker.AsyncMock(
side_effect=mock_find_first_side_effect
)
mock_store_agent.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
# Mock Profile prisma call
mock_profile = mocker.MagicMock()
@@ -139,7 +105,7 @@ async def test_get_store_agent_details(mocker):
return_value=mock_profile
)
# Mock StoreListing prisma call
# Mock StoreListing prisma call - this is what was missing
mock_store_listing_db = mocker.patch("prisma.models.StoreListing.prisma")
mock_store_listing_db.return_value.find_first = mocker.AsyncMock(
return_value=mock_store_listing
@@ -148,25 +114,16 @@ async def test_get_store_agent_details(mocker):
# Call function
result = await db.get_store_agent_details("creator", "test-agent")
# Verify results - should use active version data
# Verify results
assert result.slug == "test-agent"
assert result.agent_name == "Test Agent Active" # From active version
assert result.agent_name == "Test Agent"
assert result.active_version_id == "active-version-id"
assert result.has_approved_version is True
assert (
result.store_listing_version_id == "active-version-id"
) # Should be active version ID
# Verify mocks called correctly - now expecting 2 calls
assert mock_store_agent.return_value.find_first.call_count == 2
# Check the specific calls
calls = mock_store_agent.return_value.find_first.call_args_list
assert calls[0] == mocker.call(
# Verify mocks called correctly
mock_store_agent.return_value.find_first.assert_called_once_with(
where={"creator_username": "creator", "slug": "test-agent"}
)
assert calls[1] == mocker.call(where={"storeListingVersionId": "active-version-id"})
mock_store_listing_db.return_value.find_first.assert_called_once()

View File

@@ -49,7 +49,6 @@ class StoreAgentDetails(pydantic.BaseModel):
creator_avatar: str
sub_heading: str
description: str
instructions: str | None = None
categories: list[str]
runs: int
rating: float
@@ -104,7 +103,6 @@ class StoreSubmission(pydantic.BaseModel):
sub_heading: str
slug: str
description: str
instructions: str | None = None
image_urls: list[str]
date_submitted: datetime.datetime
status: prisma.enums.SubmissionStatus
@@ -159,7 +157,6 @@ class StoreSubmissionRequest(pydantic.BaseModel):
video_url: str | None = None
image_urls: list[str] = []
description: str = ""
instructions: str | None = None
categories: list[str] = []
changes_summary: str | None = None
recommended_schedule_cron: str | None = None
@@ -171,7 +168,6 @@ class StoreSubmissionEditRequest(pydantic.BaseModel):
video_url: str | None = None
image_urls: list[str] = []
description: str = ""
instructions: str | None = None
categories: list[str] = []
changes_summary: str | None = None
recommended_schedule_cron: str | None = None

View File

@@ -6,7 +6,6 @@ import urllib.parse
import autogpt_libs.auth
import fastapi
import fastapi.responses
from autogpt_libs.utils.cache import cached
import backend.data.graph
import backend.server.v2.store.db
@@ -21,117 +20,6 @@ logger = logging.getLogger(__name__)
router = fastapi.APIRouter()
##############################################
############### Caches #######################
##############################################
# Cache user profiles for 1 hour per user
@cached(maxsize=1000, ttl_seconds=3600)
async def _get_cached_user_profile(user_id: str):
"""Cached helper to get user profile."""
return await backend.server.v2.store.db.get_user_profile(user_id)
# Cache store agents list for 15 minutes
# Different cache entries for different query combinations
@cached(maxsize=5000, ttl_seconds=900)
async def _get_cached_store_agents(
featured: bool,
creator: str | None,
sorted_by: str | None,
search_query: str | None,
category: str | None,
page: int,
page_size: int,
):
"""Cached helper to get store agents."""
return await backend.server.v2.store.db.get_store_agents(
featured=featured,
creators=[creator] if creator else None,
sorted_by=sorted_by,
search_query=search_query,
category=category,
page=page,
page_size=page_size,
)
# Cache individual agent details for 15 minutes
@cached(maxsize=200, ttl_seconds=900)
async def _get_cached_agent_details(username: str, agent_name: str):
"""Cached helper to get agent details."""
return await backend.server.v2.store.db.get_store_agent_details(
username=username, agent_name=agent_name
)
# Cache agent graphs for 1 hour
@cached(maxsize=200, ttl_seconds=3600)
async def _get_cached_agent_graph(store_listing_version_id: str):
"""Cached helper to get agent graph."""
return await backend.server.v2.store.db.get_available_graph(
store_listing_version_id
)
# Cache agent by version for 1 hour
@cached(maxsize=200, ttl_seconds=3600)
async def _get_cached_store_agent_by_version(store_listing_version_id: str):
"""Cached helper to get store agent by version ID."""
return await backend.server.v2.store.db.get_store_agent_by_version_id(
store_listing_version_id
)
# Cache creators list for 1 hour
@cached(maxsize=200, ttl_seconds=3600)
async def _get_cached_store_creators(
featured: bool,
search_query: str | None,
sorted_by: str | None,
page: int,
page_size: int,
):
"""Cached helper to get store creators."""
return await backend.server.v2.store.db.get_store_creators(
featured=featured,
search_query=search_query,
sorted_by=sorted_by,
page=page,
page_size=page_size,
)
# Cache individual creator details for 1 hour
@cached(maxsize=100, ttl_seconds=3600)
async def _get_cached_creator_details(username: str):
"""Cached helper to get creator details."""
return await backend.server.v2.store.db.get_store_creator_details(
username=username.lower()
)
# Cache user's own agents for 5 mins (shorter TTL as this changes more frequently)
@cached(maxsize=500, ttl_seconds=300)
async def _get_cached_my_agents(user_id: str, page: int, page_size: int):
"""Cached helper to get user's agents."""
return await backend.server.v2.store.db.get_my_agents(
user_id, page=page, page_size=page_size
)
# Cache user's submissions for 1 hour (shorter TTL as this changes frequently)
@cached(maxsize=500, ttl_seconds=3600)
async def _get_cached_submissions(user_id: str, page: int, page_size: int):
"""Cached helper to get user's submissions."""
return await backend.server.v2.store.db.get_store_submissions(
user_id=user_id,
page=page,
page_size=page_size,
)
##############################################
############### Profile Endpoints ############
##############################################
@@ -149,10 +37,9 @@ async def get_profile(
):
"""
Get the profile details for the authenticated user.
Cached for 1 hour per user.
"""
try:
profile = await _get_cached_user_profile(user_id)
profile = await backend.server.v2.store.db.get_user_profile(user_id)
if profile is None:
return fastapi.responses.JSONResponse(
status_code=404,
@@ -198,8 +85,6 @@ async def update_or_create_profile(
updated_profile = await backend.server.v2.store.db.update_profile(
user_id=user_id, profile=profile
)
# Clear the cache for this user after profile update
_get_cached_user_profile.cache_delete(user_id)
return updated_profile
except Exception as e:
logger.exception("Failed to update profile for user %s: %s", user_id, e)
@@ -234,7 +119,6 @@ async def get_agents(
):
"""
Get a paginated list of agents from the store with optional filtering and sorting.
Results are cached for 15 minutes.
Args:
featured (bool, optional): Filter to only show featured agents. Defaults to False.
@@ -270,9 +154,9 @@ async def get_agents(
)
try:
agents = await _get_cached_store_agents(
agents = await backend.server.v2.store.db.get_store_agents(
featured=featured,
creator=creator,
creators=[creator] if creator else None,
sorted_by=sorted_by,
search_query=search_query,
category=category,
@@ -299,8 +183,7 @@ async def get_agents(
)
async def get_agent(username: str, agent_name: str):
"""
This is only used on the AgentDetails Page.
Results are cached for 15 minutes.
This is only used on the AgentDetails Page
It returns the store listing agents details.
"""
@@ -308,7 +191,7 @@ async def get_agent(username: str, agent_name: str):
username = urllib.parse.unquote(username).lower()
# URL decode the agent name since it comes from the URL path
agent_name = urllib.parse.unquote(agent_name).lower()
agent = await _get_cached_agent_details(
agent = await backend.server.v2.store.db.get_store_agent_details(
username=username, agent_name=agent_name
)
return agent
@@ -331,10 +214,11 @@ async def get_agent(username: str, agent_name: str):
async def get_graph_meta_by_store_listing_version_id(store_listing_version_id: str):
"""
Get Agent Graph from Store Listing Version ID.
Results are cached for 1 hour.
"""
try:
graph = await _get_cached_agent_graph(store_listing_version_id)
graph = await backend.server.v2.store.db.get_available_graph(
store_listing_version_id
)
return graph
except Exception:
logger.exception("Exception occurred whilst getting agent graph")
@@ -354,10 +238,11 @@ async def get_graph_meta_by_store_listing_version_id(store_listing_version_id: s
async def get_store_agent(store_listing_version_id: str):
"""
Get Store Agent Details from Store Listing Version ID.
Results are cached for 1 hour.
"""
try:
agent = await _get_cached_store_agent_by_version(store_listing_version_id)
agent = await backend.server.v2.store.db.get_store_agent_by_version_id(
store_listing_version_id
)
return agent
except Exception:
logger.exception("Exception occurred whilst getting store agent")
@@ -394,7 +279,7 @@ async def create_review(
"""
try:
username = urllib.parse.unquote(username).lower()
agent_name = urllib.parse.unquote(agent_name).lower()
agent_name = urllib.parse.unquote(agent_name)
# Create the review
created_review = await backend.server.v2.store.db.create_store_review(
user_id=user_id,
@@ -435,8 +320,6 @@ async def get_creators(
- Home Page Featured Creators
- Search Results Page
Results are cached for 1 hour.
---
To support this functionality we need:
@@ -455,7 +338,7 @@ async def get_creators(
)
try:
creators = await _get_cached_store_creators(
creators = await backend.server.v2.store.db.get_store_creators(
featured=featured,
search_query=search_query,
sorted_by=sorted_by,
@@ -481,13 +364,14 @@ async def get_creator(
username: str,
):
"""
Get the details of a creator.
Results are cached for 1 hour.
Get the details of a creator
- Creator Details Page
"""
try:
username = urllib.parse.unquote(username).lower()
creator = await _get_cached_creator_details(username=username)
creator = await backend.server.v2.store.db.get_store_creator_details(
username=username.lower()
)
return creator
except Exception:
logger.exception("Exception occurred whilst getting creator details")
@@ -502,8 +386,6 @@ async def get_creator(
############################################
############# Store Submissions ###############
############################################
@router.get(
"/myagents",
summary="Get my agents",
@@ -516,12 +398,10 @@ async def get_my_agents(
page: typing.Annotated[int, fastapi.Query(ge=1)] = 1,
page_size: typing.Annotated[int, fastapi.Query(ge=1)] = 20,
):
"""
Get user's own agents.
Results are cached for 5 minutes per user.
"""
try:
agents = await _get_cached_my_agents(user_id, page=page, page_size=page_size)
agents = await backend.server.v2.store.db.get_my_agents(
user_id, page=page, page_size=page_size
)
return agents
except Exception:
logger.exception("Exception occurred whilst getting my agents")
@@ -557,14 +437,6 @@ async def delete_submission(
user_id=user_id,
submission_id=submission_id,
)
# Clear submissions cache for this specific user after deletion
if result:
# Clear user's own agents cache - we don't know all page/size combinations
for page in range(1, 20):
# Clear user's submissions cache for common defaults
_get_cached_submissions.cache_delete(user_id, page=page, page_size=20)
return result
except Exception:
logger.exception("Exception occurred whilst deleting store submission")
@@ -588,7 +460,6 @@ async def get_submissions(
):
"""
Get a paginated list of store submissions for the authenticated user.
Results are cached for 1 hour per user.
Args:
user_id (str): ID of the authenticated user
@@ -611,8 +482,10 @@ async def get_submissions(
status_code=422, detail="Page size must be greater than 0"
)
try:
listings = await _get_cached_submissions(
user_id, page=page, page_size=page_size
listings = await backend.server.v2.store.db.get_store_submissions(
user_id=user_id,
page=page,
page_size=page_size,
)
return listings
except Exception:
@@ -650,7 +523,7 @@ async def create_submission(
HTTPException: If there is an error creating the submission
"""
try:
result = await backend.server.v2.store.db.create_store_submission(
return await backend.server.v2.store.db.create_store_submission(
user_id=user_id,
agent_id=submission_request.agent_id,
agent_version=submission_request.agent_version,
@@ -659,19 +532,11 @@ async def create_submission(
video_url=submission_request.video_url,
image_urls=submission_request.image_urls,
description=submission_request.description,
instructions=submission_request.instructions,
sub_heading=submission_request.sub_heading,
categories=submission_request.categories,
changes_summary=submission_request.changes_summary or "Initial Submission",
recommended_schedule_cron=submission_request.recommended_schedule_cron,
)
# Clear user's own agents cache - we don't know all page/size combinations
for page in range(1, 20):
# Clear user's submissions cache for common defaults
_get_cached_submissions.cache_delete(user_id, page=page, page_size=20)
return result
except Exception:
logger.exception("Exception occurred whilst creating store submission")
return fastapi.responses.JSONResponse(
@@ -706,27 +571,19 @@ async def edit_submission(
Raises:
HTTPException: If there is an error editing the submission
"""
result = await backend.server.v2.store.db.edit_store_submission(
return await backend.server.v2.store.db.edit_store_submission(
user_id=user_id,
store_listing_version_id=store_listing_version_id,
name=submission_request.name,
video_url=submission_request.video_url,
image_urls=submission_request.image_urls,
description=submission_request.description,
instructions=submission_request.instructions,
sub_heading=submission_request.sub_heading,
categories=submission_request.categories,
changes_summary=submission_request.changes_summary,
recommended_schedule_cron=submission_request.recommended_schedule_cron,
)
# Clear user's own agents cache - we don't know all page/size combinations
for page in range(1, 20):
# Clear user's submissions cache for common defaults
_get_cached_submissions.cache_delete(user_id, page=page, page_size=20)
return result
@router.post(
"/submissions/media",
@@ -878,63 +735,3 @@ async def download_agent_file(
return fastapi.responses.FileResponse(
tmp_file.name, filename=file_name, media_type="application/json"
)
##############################################
############### Cache Management #############
##############################################
@router.get(
"/metrics/cache",
summary="Get cache metrics in Prometheus format",
tags=["store", "metrics"],
response_class=fastapi.responses.PlainTextResponse,
)
async def get_cache_metrics():
"""
Get cache metrics in Prometheus text format.
Returns Prometheus-compatible metrics for monitoring cache performance.
Metrics include size, maxsize, TTL, and hit rate for each cache.
Returns:
str: Prometheus-formatted metrics text
"""
metrics = []
# Helper to add metrics for a cache
def add_cache_metrics(cache_name: str, cache_func):
info = cache_func.cache_info()
# Cache size metric (dynamic - changes as items are cached/expired)
metrics.append(f'store_cache_entries{{cache="{cache_name}"}} {info["size"]}')
# Cache utilization percentage (dynamic - useful for monitoring)
utilization = (
(info["size"] / info["maxsize"] * 100) if info["maxsize"] > 0 else 0
)
metrics.append(
f'store_cache_utilization_percent{{cache="{cache_name}"}} {utilization:.2f}'
)
# Add metrics for each cache
add_cache_metrics("user_profile", _get_cached_user_profile)
add_cache_metrics("store_agents", _get_cached_store_agents)
add_cache_metrics("agent_details", _get_cached_agent_details)
add_cache_metrics("agent_graph", _get_cached_agent_graph)
add_cache_metrics("agent_by_version", _get_cached_store_agent_by_version)
add_cache_metrics("store_creators", _get_cached_store_creators)
add_cache_metrics("creator_details", _get_cached_creator_details)
add_cache_metrics("my_agents", _get_cached_my_agents)
add_cache_metrics("submissions", _get_cached_submissions)
# Add metadata/help text at the beginning
prometheus_output = [
"# HELP store_cache_entries Number of entries currently in cache",
"# TYPE store_cache_entries gauge",
"# HELP store_cache_utilization_percent Cache utilization as percentage (0-100)",
"# TYPE store_cache_utilization_percent gauge",
"", # Empty line before metrics
]
prometheus_output.extend(metrics)
return "\n".join(prometheus_output)

View File

@@ -1,351 +0,0 @@
#!/usr/bin/env python3
"""
Test suite for verifying cache_delete functionality in store routes.
Tests that specific cache entries can be deleted while preserving others.
"""
import datetime
from unittest.mock import AsyncMock, patch
import pytest
from backend.server.v2.store import routes
from backend.server.v2.store.model import (
ProfileDetails,
StoreAgent,
StoreAgentDetails,
StoreAgentsResponse,
)
from backend.util.models import Pagination
class TestCacheDeletion:
"""Test cache deletion functionality for store routes."""
@pytest.mark.asyncio
async def test_store_agents_cache_delete(self):
"""Test that specific agent list cache entries can be deleted."""
# Mock the database function
mock_response = StoreAgentsResponse(
agents=[
StoreAgent(
slug="test-agent",
agent_name="Test Agent",
agent_image="https://example.com/image.jpg",
creator="testuser",
creator_avatar="https://example.com/avatar.jpg",
sub_heading="Test subheading",
description="Test description",
runs=100,
rating=4.5,
)
],
pagination=Pagination(
total_items=1,
total_pages=1,
current_page=1,
page_size=20,
),
)
with patch(
"backend.server.v2.store.db.get_store_agents",
new_callable=AsyncMock,
return_value=mock_response,
) as mock_db:
# Clear cache first
routes._get_cached_store_agents.cache_clear()
# First call - should hit database
result1 = await routes._get_cached_store_agents(
featured=False,
creator=None,
sorted_by=None,
search_query="test",
category=None,
page=1,
page_size=20,
)
assert mock_db.call_count == 1
assert result1.agents[0].agent_name == "Test Agent"
# Second call with same params - should use cache
await routes._get_cached_store_agents(
featured=False,
creator=None,
sorted_by=None,
search_query="test",
category=None,
page=1,
page_size=20,
)
assert mock_db.call_count == 1 # No additional DB call
# Third call with different params - should hit database
await routes._get_cached_store_agents(
featured=True, # Different param
creator=None,
sorted_by=None,
search_query="test",
category=None,
page=1,
page_size=20,
)
assert mock_db.call_count == 2 # New DB call
# Delete specific cache entry
deleted = routes._get_cached_store_agents.cache_delete(
featured=False,
creator=None,
sorted_by=None,
search_query="test",
category=None,
page=1,
page_size=20,
)
assert deleted is True # Entry was deleted
# Try to delete non-existent entry
deleted = routes._get_cached_store_agents.cache_delete(
featured=False,
creator="nonexistent",
sorted_by=None,
search_query="test",
category=None,
page=1,
page_size=20,
)
assert deleted is False # Entry didn't exist
# Call with deleted params - should hit database again
await routes._get_cached_store_agents(
featured=False,
creator=None,
sorted_by=None,
search_query="test",
category=None,
page=1,
page_size=20,
)
assert mock_db.call_count == 3 # New DB call after deletion
# Call with featured=True - should still be cached
await routes._get_cached_store_agents(
featured=True,
creator=None,
sorted_by=None,
search_query="test",
category=None,
page=1,
page_size=20,
)
assert mock_db.call_count == 3 # No additional DB call
@pytest.mark.asyncio
async def test_agent_details_cache_delete(self):
"""Test that specific agent details cache entries can be deleted."""
mock_response = StoreAgentDetails(
store_listing_version_id="version1",
slug="test-agent",
agent_name="Test Agent",
agent_video="https://example.com/video.mp4",
agent_image=["https://example.com/image.jpg"],
creator="testuser",
creator_avatar="https://example.com/avatar.jpg",
sub_heading="Test subheading",
description="Test description",
categories=["productivity"],
runs=100,
rating=4.5,
versions=[],
last_updated=datetime.datetime(2024, 1, 1),
)
with patch(
"backend.server.v2.store.db.get_store_agent_details",
new_callable=AsyncMock,
return_value=mock_response,
) as mock_db:
# Clear cache first
routes._get_cached_agent_details.cache_clear()
# First call - should hit database
await routes._get_cached_agent_details(
username="testuser", agent_name="testagent"
)
assert mock_db.call_count == 1
# Second call - should use cache
await routes._get_cached_agent_details(
username="testuser", agent_name="testagent"
)
assert mock_db.call_count == 1 # No additional DB call
# Delete specific entry
deleted = routes._get_cached_agent_details.cache_delete(
username="testuser", agent_name="testagent"
)
assert deleted is True
# Call again - should hit database
await routes._get_cached_agent_details(
username="testuser", agent_name="testagent"
)
assert mock_db.call_count == 2 # New DB call after deletion
@pytest.mark.asyncio
async def test_user_profile_cache_delete(self):
"""Test that user profile cache entries can be deleted."""
mock_response = ProfileDetails(
name="Test User",
username="testuser",
description="Test profile",
links=["https://example.com"],
)
with patch(
"backend.server.v2.store.db.get_user_profile",
new_callable=AsyncMock,
return_value=mock_response,
) as mock_db:
# Clear cache first
routes._get_cached_user_profile.cache_clear()
# First call - should hit database
await routes._get_cached_user_profile("user123")
assert mock_db.call_count == 1
# Second call - should use cache
await routes._get_cached_user_profile("user123")
assert mock_db.call_count == 1
# Different user - should hit database
await routes._get_cached_user_profile("user456")
assert mock_db.call_count == 2
# Delete specific user's cache
deleted = routes._get_cached_user_profile.cache_delete("user123")
assert deleted is True
# user123 should hit database again
await routes._get_cached_user_profile("user123")
assert mock_db.call_count == 3
# user456 should still be cached
await routes._get_cached_user_profile("user456")
assert mock_db.call_count == 3 # No additional DB call
@pytest.mark.asyncio
async def test_cache_info_after_deletions(self):
"""Test that cache_info correctly reflects deletions."""
# Clear all caches first
routes._get_cached_store_agents.cache_clear()
mock_response = StoreAgentsResponse(
agents=[],
pagination=Pagination(
total_items=0,
total_pages=1,
current_page=1,
page_size=20,
),
)
with patch(
"backend.server.v2.store.db.get_store_agents",
new_callable=AsyncMock,
return_value=mock_response,
):
# Add multiple entries
for i in range(5):
await routes._get_cached_store_agents(
featured=False,
creator=f"creator{i}",
sorted_by=None,
search_query=None,
category=None,
page=1,
page_size=20,
)
# Check cache size
info = routes._get_cached_store_agents.cache_info()
assert info["size"] == 5
# Delete some entries
for i in range(2):
deleted = routes._get_cached_store_agents.cache_delete(
featured=False,
creator=f"creator{i}",
sorted_by=None,
search_query=None,
category=None,
page=1,
page_size=20,
)
assert deleted is True
# Check cache size after deletion
info = routes._get_cached_store_agents.cache_info()
assert info["size"] == 3
@pytest.mark.asyncio
async def test_cache_delete_with_complex_params(self):
"""Test cache deletion with various parameter combinations."""
mock_response = StoreAgentsResponse(
agents=[],
pagination=Pagination(
total_items=0,
total_pages=1,
current_page=1,
page_size=20,
),
)
with patch(
"backend.server.v2.store.db.get_store_agents",
new_callable=AsyncMock,
return_value=mock_response,
) as mock_db:
routes._get_cached_store_agents.cache_clear()
# Test with all parameters
await routes._get_cached_store_agents(
featured=True,
creator="testuser",
sorted_by="rating",
search_query="AI assistant",
category="productivity",
page=2,
page_size=50,
)
assert mock_db.call_count == 1
# Delete with exact same parameters
deleted = routes._get_cached_store_agents.cache_delete(
featured=True,
creator="testuser",
sorted_by="rating",
search_query="AI assistant",
category="productivity",
page=2,
page_size=50,
)
assert deleted is True
# Try to delete with slightly different parameters
deleted = routes._get_cached_store_agents.cache_delete(
featured=True,
creator="testuser",
sorted_by="rating",
search_query="AI assistant",
category="productivity",
page=2,
page_size=51, # Different page_size
)
assert deleted is False # Different parameters, not in cache
if __name__ == "__main__":
# Run the tests
pytest.main([__file__, "-v"])

View File

@@ -11,10 +11,6 @@ from starlette.middleware.cors import CORSMiddleware
from backend.data.execution import AsyncRedisExecutionEventBus
from backend.data.user import DEFAULT_USER_ID
from backend.monitoring.instrumentation import (
instrument_fastapi,
update_websocket_connections,
)
from backend.server.conn_manager import ConnectionManager
from backend.server.model import (
WSMessage,
@@ -42,15 +38,6 @@ docs_url = "/docs" if settings.config.app_env == AppEnvironment.LOCAL else None
app = FastAPI(lifespan=lifespan, docs_url=docs_url)
_connection_manager = None
# Add Prometheus instrumentation
instrument_fastapi(
app,
service_name="websocket-server",
expose_endpoint=True,
endpoint="/metrics",
include_in_schema=settings.config.app_env == AppEnvironment.LOCAL,
)
def get_connection_manager():
global _connection_manager
@@ -229,10 +216,6 @@ async def websocket_router(
if not user_id:
return
await manager.connect_socket(websocket)
# Track WebSocket connection
update_websocket_connections(user_id, 1)
try:
while True:
data = await websocket.receive_text()
@@ -303,8 +286,6 @@ async def websocket_router(
except WebSocketDisconnect:
manager.disconnect_socket(websocket)
logger.debug("WebSocket client disconnected")
finally:
update_websocket_connections(user_id, -1)
@app.get("/")
@@ -314,14 +295,17 @@ async def health():
class WebsocketServer(AppProcess):
def run(self):
logger.info(f"CORS allow origins: {settings.config.backend_cors_allow_origins}")
server_app = CORSMiddleware(
app=app,
allow_origins=settings.config.backend_cors_allow_origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
if settings.config.enable_cors_all_origins:
server_app = CORSMiddleware(
app=app,
allow_origins=settings.config.backend_cors_allow_origins,
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
else:
logger.info("CORS is disabled")
server_app = app
uvicorn.run(
server_app,

View File

@@ -2,9 +2,10 @@
Centralized service client helpers with thread caching.
"""
from functools import cache
from typing import TYPE_CHECKING
from autogpt_libs.utils.cache import cached, thread_cached
from autogpt_libs.utils.cache import async_cache, thread_cached
from backend.util.settings import Settings
@@ -118,7 +119,7 @@ def get_integration_credentials_store() -> "IntegrationCredentialsStore":
# ============ Supabase Clients ============ #
@cached()
@cache
def get_supabase() -> "Client":
"""Get a process-cached synchronous Supabase client instance."""
from supabase import create_client
@@ -128,7 +129,7 @@ def get_supabase() -> "Client":
)
@cached()
@async_cache
async def get_async_supabase() -> "AClient":
"""Get a process-cached asynchronous Supabase client instance."""
from supabase import create_async_client

View File

@@ -9,7 +9,6 @@ import uuid
from datetime import datetime, timedelta, timezone
from typing import Tuple
import aiohttp
from gcloud.aio import storage as async_gcs_storage
from google.cloud import storage as gcs_storage
@@ -39,59 +38,20 @@ class CloudStorageHandler:
self.config = config
self._async_gcs_client = None
self._sync_gcs_client = None # Only for signed URLs
self._session = None
async def _get_async_gcs_client(self):
"""Get or create async GCS client, ensuring it's created in proper async context."""
# Check if we already have a client
if self._async_gcs_client is not None:
return self._async_gcs_client
current_task = asyncio.current_task()
if not current_task:
# If we're not in a task, create a temporary client
logger.warning(
"[CloudStorage] Creating GCS client outside of task context - using temporary client"
)
timeout = aiohttp.ClientTimeout(total=300)
session = aiohttp.ClientSession(
timeout=timeout,
connector=aiohttp.TCPConnector(limit=100, force_close=False),
)
return async_gcs_storage.Storage(session=session)
# Create a reusable session with proper configuration
# Key fix: Don't set timeout on session, let gcloud-aio handle it
self._session = aiohttp.ClientSession(
connector=aiohttp.TCPConnector(
limit=100, # Connection pool limit
force_close=False, # Reuse connections
enable_cleanup_closed=True,
)
)
# Create the GCS client with our session
# The key is NOT setting timeout on the session but letting the library handle it
self._async_gcs_client = async_gcs_storage.Storage(session=self._session)
def _get_async_gcs_client(self):
"""Lazy initialization of async GCS client."""
if self._async_gcs_client is None:
# Use Application Default Credentials (ADC)
self._async_gcs_client = async_gcs_storage.Storage()
return self._async_gcs_client
async def close(self):
"""Close all client connections properly."""
if self._async_gcs_client is not None:
try:
await self._async_gcs_client.close()
except Exception as e:
logger.warning(f"[CloudStorage] Error closing GCS client: {e}")
await self._async_gcs_client.close()
self._async_gcs_client = None
if self._session is not None:
try:
await self._session.close()
except Exception as e:
logger.warning(f"[CloudStorage] Error closing session: {e}")
self._session = None
async def __aenter__(self):
"""Async context manager entry."""
return self
@@ -181,7 +141,7 @@ class CloudStorageHandler:
if user_id and graph_exec_id:
raise ValueError("Provide either user_id OR graph_exec_id, not both")
async_client = await self._get_async_gcs_client()
async_client = self._get_async_gcs_client()
# Generate unique path with appropriate scope
unique_id = str(uuid.uuid4())
@@ -243,15 +203,6 @@ class CloudStorageHandler:
self, path: str, user_id: str | None = None, graph_exec_id: str | None = None
) -> bytes:
"""Retrieve file from Google Cloud Storage with authorization."""
# Log context for debugging
current_task = asyncio.current_task()
logger.info(
f"[CloudStorage]"
f"_retrieve_file_gcs called - "
f"current_task: {current_task}, "
f"in_task: {current_task is not None}"
)
# Parse bucket and blob name from path
parts = path.split("/", 1)
if len(parts) != 2:
@@ -262,65 +213,13 @@ class CloudStorageHandler:
# Authorization check
self._validate_file_access(blob_name, user_id, graph_exec_id)
# Use a fresh client for each download to avoid session issues
# This is less efficient but more reliable with the executor's event loop
logger.info("[CloudStorage] Creating fresh GCS client for download")
async_client = self._get_async_gcs_client()
# Create a new session specifically for this download
session = aiohttp.ClientSession(
connector=aiohttp.TCPConnector(limit=10, force_close=True)
)
async_client = None
try:
# Create a new GCS client with the fresh session
async_client = async_gcs_storage.Storage(session=session)
logger.info(
f"[CloudStorage] About to download from GCS - bucket: {bucket_name}, blob: {blob_name}"
)
# Download content using the fresh client
# Download content using pure async client
content = await async_client.download(bucket_name, blob_name)
logger.info(
f"[CloudStorage] GCS download successful - size: {len(content)} bytes"
)
# Clean up
await async_client.close()
await session.close()
return content
except Exception as e:
# Always try to clean up
if async_client is not None:
try:
await async_client.close()
except Exception as cleanup_error:
logger.warning(
f"[CloudStorage] Error closing GCS client: {cleanup_error}"
)
try:
await session.close()
except Exception as cleanup_error:
logger.warning(f"[CloudStorage] Error closing session: {cleanup_error}")
# Log the specific error for debugging
logger.error(
f"[CloudStorage] GCS download failed - error: {str(e)}, "
f"error_type: {type(e).__name__}, "
f"bucket: {bucket_name}, blob: redacted for privacy"
)
# Special handling for timeout error
if "Timeout context manager" in str(e):
logger.critical(
f"[CloudStorage] TIMEOUT ERROR in GCS download! "
f"current_task: {current_task}, "
f"bucket: {bucket_name}, blob: redacted for privacy"
)
# Convert gcloud-aio exceptions to standard ones
if "404" in str(e) or "Not Found" in str(e):
raise FileNotFoundError(f"File not found: gcs://{path}")
@@ -404,7 +303,7 @@ class CloudStorageHandler:
# Legacy uploads directory (uploads/*) - allow for backwards compatibility with warning
# Note: We already validated it starts with "uploads/" above, so this is guaranteed to match
logger.warning(f"[CloudStorage] Accessing legacy upload path: {blob_name}")
logger.warning(f"Accessing legacy upload path: {blob_name}")
return
async def generate_signed_url(
@@ -492,7 +391,7 @@ class CloudStorageHandler:
if not self.config.gcs_bucket_name:
raise ValueError("GCS_BUCKET_NAME not configured")
async_client = await self._get_async_gcs_client()
async_client = self._get_async_gcs_client()
current_time = datetime.now(timezone.utc)
try:
@@ -532,7 +431,7 @@ class CloudStorageHandler:
except Exception as e:
# Log specific errors for debugging
logger.warning(
f"[CloudStorage] Failed to process file {blob_name} during cleanup: {e}"
f"Failed to process file {blob_name} during cleanup: {e}"
)
# Skip files with invalid metadata or delete errors
pass
@@ -548,7 +447,7 @@ class CloudStorageHandler:
except Exception as e:
# Log the error for debugging but continue operation
logger.error(f"[CloudStorage] Cleanup operation failed: {e}")
logger.error(f"Cleanup operation failed: {e}")
# Return 0 - we'll try again next cleanup cycle
return 0
@@ -577,7 +476,7 @@ class CloudStorageHandler:
bucket_name, blob_name = parts
async_client = await self._get_async_gcs_client()
async_client = self._get_async_gcs_client()
try:
# Get object metadata using pure async client
@@ -591,15 +490,11 @@ class CloudStorageHandler:
except Exception as e:
# If file doesn't exist or we can't read metadata
if "404" in str(e) or "Not Found" in str(e):
logger.warning(
f"[CloudStorage] File not found during expiration check: {blob_name}"
)
logger.debug(f"File not found during expiration check: {blob_name}")
return True # File doesn't exist, consider it expired
# Log other types of errors for debugging
logger.warning(
f"[CloudStorage] Failed to check expiration for {blob_name}: {e}"
)
logger.warning(f"Failed to check expiration for {blob_name}: {e}")
# If we can't read metadata for other reasons, assume not expired
return False
@@ -649,15 +544,11 @@ async def cleanup_expired_files_async() -> int:
# Use cleanup lock to prevent concurrent cleanup operations
async with _cleanup_lock:
try:
logger.info(
"[CloudStorage] Starting cleanup of expired cloud storage files"
)
logger.info("Starting cleanup of expired cloud storage files")
handler = await get_cloud_storage_handler()
deleted_count = await handler.delete_expired_files()
logger.info(
f"[CloudStorage] Cleaned up {deleted_count} expired files from cloud storage"
)
logger.info(f"Cleaned up {deleted_count} expired files from cloud storage")
return deleted_count
except Exception as e:
logger.error(f"[CloudStorage] Error during cloud storage cleanup: {e}")
logger.error(f"Error during cloud storage cleanup: {e}")
return 0

View File

@@ -72,17 +72,16 @@ class TestCloudStorageHandler:
assert call_args[0][2] == content # file content
assert "metadata" in call_args[1] # metadata argument
@patch("backend.util.cloud_storage.async_gcs_storage.Storage")
@patch.object(CloudStorageHandler, "_get_async_gcs_client")
@pytest.mark.asyncio
async def test_retrieve_file_gcs(self, mock_storage_class, handler):
async def test_retrieve_file_gcs(self, mock_get_async_client, handler):
"""Test retrieving file from GCS."""
# Mock async GCS client instance
# Mock async GCS client
mock_async_client = AsyncMock()
mock_storage_class.return_value = mock_async_client
mock_get_async_client.return_value = mock_async_client
# Mock the download and close methods
# Mock the download method
mock_async_client.download = AsyncMock(return_value=b"test content")
mock_async_client.close = AsyncMock()
result = await handler.retrieve_file(
"gcs://test-bucket/uploads/system/uuid123/file.txt"
@@ -93,17 +92,16 @@ class TestCloudStorageHandler:
"test-bucket", "uploads/system/uuid123/file.txt"
)
@patch("backend.util.cloud_storage.async_gcs_storage.Storage")
@patch.object(CloudStorageHandler, "_get_async_gcs_client")
@pytest.mark.asyncio
async def test_retrieve_file_not_found(self, mock_storage_class, handler):
async def test_retrieve_file_not_found(self, mock_get_async_client, handler):
"""Test retrieving non-existent file from GCS."""
# Mock async GCS client instance
# Mock async GCS client
mock_async_client = AsyncMock()
mock_storage_class.return_value = mock_async_client
mock_get_async_client.return_value = mock_async_client
# Mock the download method to raise a 404 exception
mock_async_client.download = AsyncMock(side_effect=Exception("404 Not Found"))
mock_async_client.close = AsyncMock()
with pytest.raises(FileNotFoundError):
await handler.retrieve_file(
@@ -289,15 +287,14 @@ class TestCloudStorageHandler:
):
handler._validate_file_access("invalid/path/file.txt", "user123")
@patch("backend.util.cloud_storage.async_gcs_storage.Storage")
@patch.object(CloudStorageHandler, "_get_async_gcs_client")
@pytest.mark.asyncio
async def test_retrieve_file_with_authorization(self, mock_storage_class, handler):
async def test_retrieve_file_with_authorization(self, mock_get_client, handler):
"""Test file retrieval with authorization."""
# Mock async GCS client instance
# Mock async GCS client
mock_client = AsyncMock()
mock_storage_class.return_value = mock_client
mock_get_client.return_value = mock_client
mock_client.download = AsyncMock(return_value=b"test content")
mock_client.close = AsyncMock()
# Test successful retrieval of user's own file
result = await handler.retrieve_file(
@@ -415,19 +412,18 @@ class TestCloudStorageHandler:
"uploads/executions/exec123/uuid456/file.txt", graph_exec_id="exec456"
)
@patch("backend.util.cloud_storage.async_gcs_storage.Storage")
@patch.object(CloudStorageHandler, "_get_async_gcs_client")
@pytest.mark.asyncio
async def test_retrieve_file_with_exec_authorization(
self, mock_storage_class, handler
self, mock_get_async_client, handler
):
"""Test file retrieval with execution authorization."""
# Mock async GCS client instance
# Mock async GCS client
mock_async_client = AsyncMock()
mock_storage_class.return_value = mock_async_client
mock_get_async_client.return_value = mock_async_client
# Mock the download and close methods
# Mock the download method
mock_async_client.download = AsyncMock(return_value=b"test content")
mock_async_client.close = AsyncMock()
# Test successful retrieval of execution's own file
result = await handler.retrieve_file(

View File

@@ -5,7 +5,7 @@ from functools import wraps
from typing import Any, Awaitable, Callable, TypeVar
import ldclient
from autogpt_libs.utils.cache import cached
from autogpt_libs.utils.cache import async_ttl_cache
from fastapi import HTTPException
from ldclient import Context, LDClient
from ldclient.config import Config
@@ -72,7 +72,7 @@ def shutdown_launchdarkly() -> None:
logger.info("LaunchDarkly client closed successfully")
@cached(maxsize=1000, ttl_seconds=86400) # 1000 entries, 24 hours TTL
@async_ttl_cache(maxsize=1000, ttl_seconds=86400) # 1000 entries, 24 hours TTL
async def _fetch_user_context_data(user_id: str) -> Context:
"""
Fetch user context for LaunchDarkly from Supabase.

View File

@@ -8,14 +8,6 @@ from pydantic import BaseModel
from .type import type_match
# Try to import orjson for better performance
try:
import orjson
HAS_ORJSON = True
except ImportError:
HAS_ORJSON = False
def to_dict(data) -> dict:
if isinstance(data, BaseModel):
@@ -29,16 +21,16 @@ def dumps(data: Any, *args: Any, **kwargs: Any) -> str:
This function converts the input data to a JSON-serializable format using FastAPI's
jsonable_encoder before dumping to JSON. It handles Pydantic models, complex types,
and ensures proper serialization. Uses orjson for better performance when available.
and ensures proper serialization.
Parameters
----------
data : Any
The data to serialize. Can be any type including Pydantic models, dicts, lists, etc.
*args : Any
Additional positional arguments passed to json.dumps() (ignored if using orjson)
Additional positional arguments passed to json.dumps()
**kwargs : Any
Additional keyword arguments passed to json.dumps() (limited support with orjson)
Additional keyword arguments passed to json.dumps() (e.g., indent, separators)
Returns
-------
@@ -53,18 +45,7 @@ def dumps(data: Any, *args: Any, **kwargs: Any) -> str:
>>> dumps(pydantic_model_instance, indent=2)
'{\n "field1": "value1",\n "field2": "value2"\n}'
"""
serializable_data = to_dict(data)
if HAS_ORJSON:
# orjson is faster but has limited options support
option = 0
if kwargs.get("indent") is not None:
option |= orjson.OPT_INDENT_2
# orjson.dumps returns bytes, so we decode to str
return orjson.dumps(serializable_data, option=option).decode("utf-8")
else:
# Fallback to standard json
return json.dumps(serializable_data, *args, **kwargs)
return json.dumps(to_dict(data), *args, **kwargs)
T = TypeVar("T")
@@ -81,15 +62,9 @@ def loads(data: str | bytes, *args, **kwargs) -> Any: ...
def loads(
data: str | bytes, *args, target_type: Type[T] | None = None, **kwargs
) -> Any:
if HAS_ORJSON:
# orjson can handle both str and bytes directly
parsed = orjson.loads(data)
else:
# Standard json requires string input
if isinstance(data, bytes):
data = data.decode("utf-8")
parsed = json.loads(data, *args, **kwargs)
if isinstance(data, bytes):
data = data.decode("utf-8")
parsed = json.loads(data, *args, **kwargs)
if target_type:
return type_match(parsed, target_type)
return parsed
@@ -123,35 +98,11 @@ def convert_pydantic_to_json(output_data: Any) -> Any:
return output_data
def _sanitize_null_bytes(data: Any) -> Any:
"""
Recursively sanitize null bytes from data structures to prevent PostgreSQL 22P05 errors.
PostgreSQL cannot store null bytes (\u0000) in text fields.
"""
if isinstance(data, str):
return data.replace("\u0000", "")
elif isinstance(data, dict):
return {key: _sanitize_null_bytes(value) for key, value in data.items()}
elif isinstance(data, list):
return [_sanitize_null_bytes(item) for item in data]
elif isinstance(data, tuple):
return tuple(_sanitize_null_bytes(item) for item in data)
else:
# For other types (int, float, bool, None, etc.), return as-is
return data
def SafeJson(data: Any) -> Json:
"""
Safely serialize data and return Prisma's Json type.
Sanitizes null bytes to prevent PostgreSQL 22P05 errors.
"""
# Sanitize null bytes before serialization
sanitized_data = _sanitize_null_bytes(data)
if isinstance(sanitized_data, BaseModel):
"""Safely serialize data and return Prisma's Json type."""
if isinstance(data, BaseModel):
return Json(
sanitized_data.model_dump(
data.model_dump(
mode="json",
warnings="error",
exclude_none=True,
@@ -159,5 +110,5 @@ def SafeJson(data: Any) -> Json:
)
)
# Round-trip through JSON to ensure proper serialization with fallback for non-serializable values
json_string = dumps(sanitized_data, default=lambda v: None)
json_string = dumps(data, default=lambda v: None)
return Json(json.loads(json_string))

View File

@@ -17,37 +17,6 @@ from backend.util.process import get_service_name
logger = logging.getLogger(__name__)
# Alert threshold for excessive retries
EXCESSIVE_RETRY_THRESHOLD = 50
def _send_retry_alert(
func_name: str, attempt_number: int, exception: Exception, context: str = ""
):
"""Send alert for excessive retry attempts."""
try:
# Import here to avoid circular imports
from backend.util.clients import get_notification_manager_client
notification_client = get_notification_manager_client()
prefix = f"{context}: " if context else ""
alert_msg = (
f"🚨 Excessive Retry Alert: {prefix}'{func_name}' has failed {attempt_number} times!\n\n"
f"Error: {type(exception).__name__}: {exception}\n\n"
f"This indicates a persistent issue that requires investigation. "
f"The operation has been retrying for an extended period."
)
notification_client.discord_system_alert(alert_msg)
logger.critical(
f"ALERT SENT: Excessive retries detected for {func_name} after {attempt_number} attempts"
)
except Exception as alert_error:
logger.error(f"Failed to send retry alert: {alert_error}")
# Don't let alerting failures break the main flow
def _create_retry_callback(context: str = ""):
"""Create a retry callback with optional context."""
@@ -59,10 +28,6 @@ def _create_retry_callback(context: str = ""):
prefix = f"{context}: " if context else ""
# Send alert if we've exceeded the threshold
if attempt_number >= EXCESSIVE_RETRY_THRESHOLD:
_send_retry_alert(func_name, attempt_number, exception, context)
if retry_state.outcome.failed and retry_state.next_action is None:
# Final failure
logger.error(
@@ -138,13 +103,6 @@ def conn_retry(
def on_retry(retry_state):
prefix = _log_prefix(resource_name, conn_id)
exception = retry_state.outcome.exception()
attempt_number = retry_state.attempt_number
# Send alert if we've exceeded the threshold
if attempt_number >= EXCESSIVE_RETRY_THRESHOLD:
func_name = f"{resource_name}:{action_name}"
context = f"Connection retry {resource_name}"
_send_retry_alert(func_name, attempt_number, exception, context)
if retry_state.outcome.failed and retry_state.next_action is None:
logger.error(f"{prefix} {action_name} failed after retries: {exception}")

View File

@@ -43,7 +43,6 @@ api_host = config.pyro_host
api_comm_retry = config.pyro_client_comm_retry
api_comm_timeout = config.pyro_client_comm_timeout
api_call_timeout = config.rpc_client_call_timeout
api_comm_max_wait = config.pyro_client_max_wait
def _validate_no_prisma_objects(obj: Any, path: str = "result") -> None:
@@ -353,7 +352,7 @@ def get_service_client(
# Use preconfigured retry decorator for service communication
return create_retry_decorator(
max_attempts=api_comm_retry,
max_wait=api_comm_max_wait,
max_wait=5.0,
context="Service communication",
exclude_exceptions=(
# Don't retry these specific exceptions that won't be fixed by retrying

View File

@@ -68,13 +68,9 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
description="The default timeout in seconds, for Pyro client connections.",
)
pyro_client_comm_retry: int = Field(
default=100,
default=5,
description="The default number of retries for Pyro client connections.",
)
pyro_client_max_wait: float = Field(
default=30.0,
description="The maximum wait time in seconds for Pyro client retries.",
)
rpc_client_call_timeout: int = Field(
default=300,
description="The default timeout in seconds, for RPC client calls.",
@@ -372,6 +368,11 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
description="Maximum message size limit for communication with the message bus",
)
enable_cors_all_origins: bool = Field(
default=True,
description="Whether to enable all CORS origins",
)
backend_cors_allow_origins: List[str] = Field(default=["http://localhost:3000"])
@field_validator("backend_cors_allow_origins")
@@ -483,9 +484,6 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
)
openai_api_key: str = Field(default="", description="OpenAI API key")
openai_internal_api_key: str = Field(
default="", description="OpenAI Internal API key"
)
aiml_api_key: str = Field(default="", description="'AI/ML API' key")
anthropic_api_key: str = Field(default="", description="Anthropic API key")
groq_api_key: str = Field(default="", description="Groq API key")

View File

@@ -16,8 +16,8 @@ def format_filter_for_jinja2(value, format_string=None):
class TextFormatter:
def __init__(self, autoescape: bool = True):
self.env = SandboxedEnvironment(loader=BaseLoader(), autoescape=autoescape)
def __init__(self):
self.env = SandboxedEnvironment(loader=BaseLoader(), autoescape=True)
self.env.globals.clear()
# Instead of clearing all filters, just remove potentially unsafe ones

View File

@@ -1,18 +0,0 @@
# Load testing credentials and sensitive data
configs/pre-authenticated-tokens.js
configs/k6-credentials.env
results/
k6-cloud-results.txt
# Node.js
node_modules/
npm-debug.log*
yarn-debug.log*
yarn-error.log*
# Environment files
.env
.env.local
.env.development.local
.env.test.local
.env.production.local

View File

@@ -1,283 +0,0 @@
# AutoGPT Platform Load Tests
Clean, streamlined load testing infrastructure for the AutoGPT Platform using k6.
## 🚀 Quick Start
```bash
# 1. Set up Supabase service key (required for token generation)
export SUPABASE_SERVICE_KEY="your-supabase-service-key"
# 2. Generate pre-authenticated tokens (first time setup - creates 150+ tokens with 24-hour expiry)
node generate-tokens.js
# 3. Set up k6 cloud credentials (for cloud testing)
export K6_CLOUD_TOKEN="your-k6-cloud-token"
export K6_CLOUD_PROJECT_ID="4254406"
# 4. Verify setup and run quick test
node run-tests.js verify
# 5. Run tests locally (development/debugging)
node run-tests.js run all DEV
# 6. Run tests in k6 cloud (performance testing)
node run-tests.js cloud all DEV
```
## 📋 Unified Test Runner
The AutoGPT Platform uses a single unified test runner (`run-tests.js`) for both local and cloud execution:
### Available Tests
#### Basic Tests (Simple validation)
- **connectivity-test**: Basic connectivity and authentication validation
- **single-endpoint-test**: Individual API endpoint testing with high concurrency
#### API Tests (Core functionality)
- **core-api-test**: Core API endpoints (`/api/credits`, `/api/graphs`, `/api/blocks`, `/api/executions`)
- **graph-execution-test**: Complete graph creation and execution pipeline
#### Marketplace Tests (User-facing features)
- **marketplace-public-test**: Public marketplace browsing and search
- **marketplace-library-test**: Authenticated marketplace and user library operations
#### Comprehensive Tests (End-to-end scenarios)
- **comprehensive-test**: Complete user journey simulation with multiple operations
### Test Modes
- **Local Mode**: 5 VUs × 30s - Quick validation and debugging
- **Cloud Mode**: 80-150 VUs × 3-5m - Real performance testing
## 🛠️ Usage
### Basic Commands
```bash
# List available tests and show cloud credentials status
node run-tests.js list
# Quick setup verification
node run-tests.js verify
# Run specific test locally
node run-tests.js run core-api-test DEV
# Run multiple tests sequentially (comma-separated)
node run-tests.js run connectivity-test,core-api-test,marketplace-public-test DEV
# Run all tests locally
node run-tests.js run all DEV
# Run specific test in k6 cloud
node run-tests.js cloud core-api-test DEV
# Run all tests in k6 cloud
node run-tests.js cloud all DEV
```
### NPM Scripts
```bash
# Quick verification
npm run verify
# Run all tests locally
npm test
# Run all tests in k6 cloud
npm run cloud
```
## 🔧 Test Configuration
### Pre-Authenticated Tokens
- **Generation**: Run `node generate-tokens.js` to create tokens
- **File**: `configs/pre-authenticated-tokens.js` (gitignored for security)
- **Capacity**: 150+ tokens supporting high-concurrency testing
- **Expiry**: 24 hours (86400 seconds) - extended for long-duration testing
- **Benefit**: Eliminates Supabase auth rate limiting at scale
- **Regeneration**: Run `node generate-tokens.js` when tokens expire after 24 hours
### Environment Configuration
- **LOCAL**: `http://localhost:8006` (local development)
- **DEV**: `https://dev-api.agpt.co` (development environment)
- **PROD**: `https://api.agpt.co` (production environment - coordinate with team!)
## 📊 Performance Testing Features
### Real-Time Monitoring
- **k6 Cloud Dashboard**: Live performance metrics during cloud test execution
- **URL Tracking**: Test URLs automatically saved to `k6-cloud-results.txt`
- **Error Tracking**: Detailed failure analysis and HTTP status monitoring
- **Custom Metrics**: Request success/failure rates, response times, user journey tracking
- **Authentication Monitoring**: Tracks auth success/failure rates separately from HTTP errors
### Load Testing Capabilities
- **High Concurrency**: Up to 150+ virtual users per test
- **Authentication Scaling**: Pre-auth tokens support 150+ concurrent users (10 tokens generated by default)
- **Sequential Execution**: Multiple tests run one after another with proper delays
- **Cloud Infrastructure**: Tests run on k6 cloud servers for consistent results
- **ES Module Support**: Full ES module compatibility with modern JavaScript features
## 📈 Performance Expectations
### Validated Performance Limits
- **Core API**: 100 VUs successfully handling `/api/credits`, `/api/graphs`, `/api/blocks`, `/api/executions`
- **Graph Execution**: 80 VUs for complete workflow pipeline
- **Marketplace Browsing**: 150 VUs for public marketplace access
- **Authentication**: 150+ concurrent users with pre-authenticated tokens
### Target Metrics
- **P95 Latency**: Target < 5 seconds (marketplace), < 2 seconds (core API)
- **P99 Latency**: Target < 10 seconds (marketplace), < 5 seconds (core API)
- **Success Rate**: Target > 95% under normal load
- **Error Rate**: Target < 5% for all endpoints
## 🔍 Troubleshooting
### Common Issues
**1. Authentication Failures**
```
❌ No valid authentication token available
❌ Token has expired
```
- **Solution**: Run `node generate-tokens.js` to create fresh 24-hour tokens
- **Note**: Default generates 10 tokens (increase with `--count=50` for higher concurrency)
**2. Cloud Credentials Missing**
```
❌ Missing k6 cloud credentials
```
- **Solution**: Set `K6_CLOUD_TOKEN` and `K6_CLOUD_PROJECT_ID=4254406`
**3. Setup Verification Failed**
```
❌ Verification failed
```
- **Solution**: Check tokens exist and local API is accessible
### Required Setup
**1. Supabase Service Key (Required for all testing):**
```bash
# Get service key from environment or Kubernetes
export SUPABASE_SERVICE_KEY="your-supabase-service-key"
```
**2. Generate Pre-Authenticated Tokens (Required):**
```bash
# Creates 10 tokens with 24-hour expiry - prevents auth rate limiting
node generate-tokens.js
# Generate more tokens for higher concurrency
node generate-tokens.js --count=50
# Regenerate when tokens expire (every 24 hours)
node generate-tokens.js
```
**3. k6 Cloud Credentials (Required for cloud testing):**
```bash
export K6_CLOUD_TOKEN="your-k6-cloud-token"
export K6_CLOUD_PROJECT_ID="4254406" # AutoGPT Platform project ID
```
## 📂 File Structure
```
load-tests/
├── README.md # This documentation
├── run-tests.js # Unified test runner (MAIN ENTRY POINT)
├── generate-tokens.js # Generate pre-auth tokens
├── package.json # Node.js dependencies and scripts
├── configs/
│ ├── environment.js # Environment URLs and configuration
│ └── pre-authenticated-tokens.js # Generated tokens (gitignored)
├── tests/
│ ├── basic/
│ │ ├── connectivity-test.js # Basic connectivity validation
│ │ └── single-endpoint-test.js # Individual API endpoint testing
│ ├── api/
│ │ ├── core-api-test.js # Core authenticated API endpoints
│ │ └── graph-execution-test.js # Graph workflow pipeline testing
│ ├── marketplace/
│ │ ├── public-access-test.js # Public marketplace browsing
│ │ └── library-access-test.js # Authenticated marketplace/library
│ └── comprehensive/
│ └── platform-journey-test.js # Complete user journey simulation
├── orchestrator/
│ └── comprehensive-orchestrator.js # Full 25-test orchestration suite
├── results/ # Local test results (auto-created)
├── k6-cloud-results.txt # Cloud test URLs (auto-created)
└── *.json # Test output files (auto-created)
```
## 🎯 Best Practices
1. **Start with Verification**: Always run `node run-tests.js verify` first
2. **Local for Development**: Use `run` command for debugging and development
3. **Cloud for Performance**: Use `cloud` command for actual performance testing
4. **Monitor Real-Time**: Check k6 cloud dashboards during test execution
5. **Regenerate Tokens**: Refresh tokens every 24 hours when they expire
6. **Sequential Testing**: Use comma-separated tests for organized execution
## 🚀 Advanced Usage
### Direct k6 Execution
For granular control over individual test scripts:
```bash
# k6 Cloud execution (recommended for performance testing)
K6_ENVIRONMENT=DEV VUS=100 DURATION=5m \
k6 cloud run --env K6_ENVIRONMENT=DEV --env VUS=100 --env DURATION=5m tests/api/core-api-test.js
# Local execution with cloud output (debugging)
K6_ENVIRONMENT=DEV VUS=10 DURATION=1m \
k6 run tests/api/core-api-test.js --out cloud
# Local execution with JSON output (offline testing)
K6_ENVIRONMENT=DEV VUS=10 DURATION=1m \
k6 run tests/api/core-api-test.js --out json=results.json
```
### Custom Token Generation
```bash
# Generate specific number of tokens
node generate-tokens.js --count=200
# Generate tokens with custom timeout
node generate-tokens.js --count=100 --timeout=60
```
## 🔗 Related Documentation
- [k6 Documentation](https://k6.io/docs/)
- [AutoGPT Platform API Documentation](https://docs.agpt.co/)
- [k6 Cloud Dashboard](https://significantgravitas.grafana.net/a/k6-app/)
For questions or issues, please refer to the [AutoGPT Platform issues](https://github.com/Significant-Gravitas/AutoGPT/issues).

View File

@@ -1,141 +0,0 @@
// Environment configuration for AutoGPT Platform load tests
export const ENV_CONFIG = {
DEV: {
API_BASE_URL: "https://dev-server.agpt.co",
BUILDER_BASE_URL: "https://dev-builder.agpt.co",
WS_BASE_URL: "wss://dev-ws-server.agpt.co",
SUPABASE_URL: "https://adfjtextkuilwuhzdjpf.supabase.co",
SUPABASE_ANON_KEY:
"eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6ImFkZmp0ZXh0a3VpbHd1aHpkanBmIiwicm9sZSI6ImFub24iLCJpYXQiOjE3MzAyNTE3MDIsImV4cCI6MjA0NTgyNzcwMn0.IuQNXsHEKJNxtS9nyFeqO0BGMYN8sPiObQhuJLSK9xk",
},
LOCAL: {
API_BASE_URL: "http://localhost:8006",
BUILDER_BASE_URL: "http://localhost:3000",
WS_BASE_URL: "ws://localhost:8001",
SUPABASE_URL: "http://localhost:8000",
SUPABASE_ANON_KEY:
"eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyAgCiAgICAicm9sZSI6ICJhbm9uIiwKICAgICJpc3MiOiAic3VwYWJhc2UtZGVtbyIsCiAgICAiaWF0IjogMTY0MTc2OTIwMCwKICAgICJleHAiOiAxNzk5NTM1NjAwCn0.dc_X5iR_VP_qT0zsiyj_I_OZ2T9FtRU2BBNWN8Bu4GE",
},
PROD: {
API_BASE_URL: "https://api.agpt.co",
BUILDER_BASE_URL: "https://builder.agpt.co",
WS_BASE_URL: "wss://ws-server.agpt.co",
SUPABASE_URL: "https://supabase.agpt.co",
SUPABASE_ANON_KEY:
"eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6ImJnd3B3ZHN4YmxyeWloaW51dGJ4Iiwicm9sZSI6ImFub24iLCJpYXQiOjE3MzAyODYzMDUsImV4cCI6MjA0NTg2MjMwNX0.ISa2IofTdQIJmmX5JwKGGNajqjsD8bjaGBzK90SubE0",
},
};
// Get environment config based on K6_ENVIRONMENT variable (default: DEV)
export function getEnvironmentConfig() {
const env = __ENV.K6_ENVIRONMENT || "DEV";
return ENV_CONFIG[env];
}
// Authentication configuration
export const AUTH_CONFIG = {
// Test user credentials - REPLACE WITH ACTUAL TEST ACCOUNTS
TEST_USERS: [
{
email: "loadtest1@example.com",
password: "LoadTest123!",
user_id: "test-user-1",
},
{
email: "loadtest2@example.com",
password: "LoadTest123!",
user_id: "test-user-2",
},
{
email: "loadtest3@example.com",
password: "LoadTest123!",
user_id: "test-user-3",
},
],
// JWT token for API access (will be set during test execution)
JWT_TOKEN: null,
};
// Performance test configurations - Environment variable overrides supported
export const PERFORMANCE_CONFIG = {
// Default load test parameters (override with env vars: VUS, DURATION, RAMP_UP, RAMP_DOWN)
DEFAULT_VUS: parseInt(__ENV.VUS) || 10,
DEFAULT_DURATION: __ENV.DURATION || "2m",
DEFAULT_RAMP_UP: __ENV.RAMP_UP || "30s",
DEFAULT_RAMP_DOWN: __ENV.RAMP_DOWN || "30s",
// Stress test parameters (override with env vars: STRESS_VUS, STRESS_DURATION, etc.)
STRESS_VUS: parseInt(__ENV.STRESS_VUS) || 50,
STRESS_DURATION: __ENV.STRESS_DURATION || "5m",
STRESS_RAMP_UP: __ENV.STRESS_RAMP_UP || "1m",
STRESS_RAMP_DOWN: __ENV.STRESS_RAMP_DOWN || "1m",
// Spike test parameters (override with env vars: SPIKE_VUS, SPIKE_DURATION, etc.)
SPIKE_VUS: parseInt(__ENV.SPIKE_VUS) || 100,
SPIKE_DURATION: __ENV.SPIKE_DURATION || "30s",
SPIKE_RAMP_UP: __ENV.SPIKE_RAMP_UP || "10s",
SPIKE_RAMP_DOWN: __ENV.SPIKE_RAMP_DOWN || "10s",
// Volume test parameters (override with env vars: VOLUME_VUS, VOLUME_DURATION, etc.)
VOLUME_VUS: parseInt(__ENV.VOLUME_VUS) || 20,
VOLUME_DURATION: __ENV.VOLUME_DURATION || "10m",
VOLUME_RAMP_UP: __ENV.VOLUME_RAMP_UP || "2m",
VOLUME_RAMP_DOWN: __ENV.VOLUME_RAMP_DOWN || "2m",
// SLA thresholds (adjustable via env vars: THRESHOLD_P95, THRESHOLD_P99, etc.)
THRESHOLDS: {
http_req_duration: [
`p(95)<${__ENV.THRESHOLD_P95 || "2000"}`,
`p(99)<${__ENV.THRESHOLD_P99 || "5000"}`,
],
http_req_failed: [`rate<${__ENV.THRESHOLD_ERROR_RATE || "0.05"}`],
http_reqs: [`rate>${__ENV.THRESHOLD_RPS || "10"}`],
checks: [`rate>${__ENV.THRESHOLD_CHECK_RATE || "0.95"}`],
},
};
// Helper function to get load test configuration based on test type
export function getLoadTestConfig(testType = "default") {
const configs = {
default: {
vus: PERFORMANCE_CONFIG.DEFAULT_VUS,
duration: PERFORMANCE_CONFIG.DEFAULT_DURATION,
rampUp: PERFORMANCE_CONFIG.DEFAULT_RAMP_UP,
rampDown: PERFORMANCE_CONFIG.DEFAULT_RAMP_DOWN,
},
stress: {
vus: PERFORMANCE_CONFIG.STRESS_VUS,
duration: PERFORMANCE_CONFIG.STRESS_DURATION,
rampUp: PERFORMANCE_CONFIG.STRESS_RAMP_UP,
rampDown: PERFORMANCE_CONFIG.STRESS_RAMP_DOWN,
},
spike: {
vus: PERFORMANCE_CONFIG.SPIKE_VUS,
duration: PERFORMANCE_CONFIG.SPIKE_DURATION,
rampUp: PERFORMANCE_CONFIG.SPIKE_RAMP_UP,
rampDown: PERFORMANCE_CONFIG.SPIKE_RAMP_DOWN,
},
volume: {
vus: PERFORMANCE_CONFIG.VOLUME_VUS,
duration: PERFORMANCE_CONFIG.VOLUME_DURATION,
rampUp: PERFORMANCE_CONFIG.VOLUME_RAMP_UP,
rampDown: PERFORMANCE_CONFIG.VOLUME_RAMP_DOWN,
},
};
return configs[testType] || configs.default;
}
// Grafana Cloud K6 configuration
export const GRAFANA_CONFIG = {
PROJECT_ID: __ENV.K6_CLOUD_PROJECT_ID || "",
TOKEN: __ENV.K6_CLOUD_TOKEN || "",
// Tags for organizing test results
TEST_TAGS: {
team: "platform",
service: "autogpt-platform",
environment: __ENV.K6_ENVIRONMENT || "dev",
version: __ENV.GIT_COMMIT || "unknown",
},
};

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@@ -1,9 +0,0 @@
# k6 Cloud Credentials (EXAMPLE FILE)
# Copy this to k6-credentials.env and fill in your actual credentials
#
# Get these from: https://app.k6.io/
# - K6_CLOUD_TOKEN: Your k6 cloud API token
# - K6_CLOUD_PROJECT_ID: Your project ID
K6_CLOUD_TOKEN=your-k6-cloud-token-here
K6_CLOUD_PROJECT_ID=your-project-id-here

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@@ -1,51 +0,0 @@
// Pre-authenticated tokens for load testing (EXAMPLE FILE)
// Copy this to pre-authenticated-tokens.js and run generate-tokens.js to populate
//
// ⚠️ SECURITY: The real file contains authentication tokens
// ⚠️ DO NOT COMMIT TO GIT - Real file is gitignored
export const PRE_AUTHENTICATED_TOKENS = [
// Will be populated by generate-tokens.js with 350+ real tokens
// Example structure:
// {
// token: "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...",
// user: "loadtest4@example.com",
// generated: "2025-01-24T10:08:04.123Z",
// round: 1
// }
];
export function getPreAuthenticatedToken(vuId = 1) {
if (PRE_AUTHENTICATED_TOKENS.length === 0) {
throw new Error(
"No pre-authenticated tokens available. Run: node generate-tokens.js",
);
}
const tokenIndex = (vuId - 1) % PRE_AUTHENTICATED_TOKENS.length;
const tokenData = PRE_AUTHENTICATED_TOKENS[tokenIndex];
return {
access_token: tokenData.token,
user: { email: tokenData.user },
generated: tokenData.generated,
};
}
export function getPreAuthenticatedHeaders(vuId = 1) {
const authData = getPreAuthenticatedToken(vuId);
return {
"Content-Type": "application/json",
Authorization: `Bearer ${authData.access_token}`,
};
}
export const TOKEN_STATS = {
total: PRE_AUTHENTICATED_TOKENS.length,
users: [...new Set(PRE_AUTHENTICATED_TOKENS.map((t) => t.user))].length,
generated: PRE_AUTHENTICATED_TOKENS[0]?.generated || "unknown",
};
console.log(
`🔐 Loaded ${TOKEN_STATS.total} pre-authenticated tokens from ${TOKEN_STATS.users} users`,
);

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@@ -1,236 +0,0 @@
#!/usr/bin/env node
/**
* Generate Pre-Authenticated Tokens for Load Testing
* Creates configs/pre-authenticated-tokens.js with 350+ tokens
*
* This replaces the old token generation scripts with a clean, single script
*/
import https from "https";
import fs from "fs";
import path from "path";
// Get Supabase service key from environment (REQUIRED for token generation)
const SUPABASE_SERVICE_KEY = process.env.SUPABASE_SERVICE_KEY;
if (!SUPABASE_SERVICE_KEY) {
console.error("❌ SUPABASE_SERVICE_KEY environment variable is required");
console.error("Get service key from kubectl or environment:");
console.error('export SUPABASE_SERVICE_KEY="your-service-key"');
process.exit(1);
}
// Generate test users (loadtest4-50 are known to work)
const TEST_USERS = [];
for (let i = 4; i <= 50; i++) {
TEST_USERS.push({
email: `loadtest${i}@example.com`,
password: "password123",
});
}
console.log(
`🔐 Generating pre-authenticated tokens from ${TEST_USERS.length} users...`,
);
async function authenticateUser(user, attempt = 1) {
return new Promise((resolve) => {
const postData = JSON.stringify({
email: user.email,
password: user.password,
expires_in: 86400, // 24 hours in seconds (24 * 60 * 60)
});
const options = {
hostname: "adfjtextkuilwuhzdjpf.supabase.co",
path: "/auth/v1/token?grant_type=password",
method: "POST",
headers: {
Authorization: `Bearer ${SUPABASE_SERVICE_KEY}`,
apikey: SUPABASE_SERVICE_KEY,
"Content-Type": "application/json",
"Content-Length": postData.length,
},
};
const req = https.request(options, (res) => {
let data = "";
res.on("data", (chunk) => (data += chunk));
res.on("end", () => {
try {
if (res.statusCode === 200) {
const authData = JSON.parse(data);
resolve(authData.access_token);
} else if (res.statusCode === 429) {
// Rate limited - wait and retry
console.log(
`⏳ Rate limited for ${user.email}, waiting 5s (attempt ${attempt}/3)...`,
);
setTimeout(() => {
if (attempt < 3) {
authenticateUser(user, attempt + 1).then(resolve);
} else {
console.log(`❌ Max retries exceeded for ${user.email}`);
resolve(null);
}
}, 5000);
} else {
console.log(`❌ Auth failed for ${user.email}: ${res.statusCode}`);
resolve(null);
}
} catch (e) {
console.log(`❌ Parse error for ${user.email}:`, e.message);
resolve(null);
}
});
});
req.on("error", (err) => {
console.log(`❌ Request error for ${user.email}:`, err.message);
resolve(null);
});
req.write(postData);
req.end();
});
}
async function generateTokens() {
console.log("🚀 Starting token generation...");
console.log("Rate limit aware - this will take ~10-15 minutes");
console.log("===========================================\n");
const tokens = [];
const startTime = Date.now();
// Generate tokens - configurable via --count argument or default to 150
const targetTokens =
parseInt(
process.argv.find((arg) => arg.startsWith("--count="))?.split("=")[1],
) ||
parseInt(process.env.TOKEN_COUNT) ||
150;
const tokensPerUser = Math.ceil(targetTokens / TEST_USERS.length);
console.log(
`📊 Generating ${tokensPerUser} tokens per user (${TEST_USERS.length} users) - Target: ${targetTokens}\n`,
);
for (let round = 1; round <= tokensPerUser; round++) {
console.log(`🔄 Round ${round}/${tokensPerUser}:`);
for (
let i = 0;
i < TEST_USERS.length && tokens.length < targetTokens;
i++
) {
const user = TEST_USERS[i];
process.stdout.write(` ${user.email.padEnd(25)} ... `);
const token = await authenticateUser(user);
if (token) {
tokens.push({
token,
user: user.email,
generated: new Date().toISOString(),
round: round,
});
console.log(`✅ (${tokens.length}/${targetTokens})`);
} else {
console.log(``);
}
// Respect rate limits - wait 500ms between requests
if (tokens.length < targetTokens) {
await new Promise((resolve) => setTimeout(resolve, 500));
}
}
if (tokens.length >= targetTokens) break;
// Wait longer between rounds
if (round < tokensPerUser) {
console.log(` ⏸️ Waiting 3s before next round...\n`);
await new Promise((resolve) => setTimeout(resolve, 3000));
}
}
const duration = Math.round((Date.now() - startTime) / 1000);
console.log(`\n✅ Generated ${tokens.length} tokens in ${duration}s`);
// Create configs directory if it doesn't exist
const configsDir = path.join(process.cwd(), "configs");
if (!fs.existsSync(configsDir)) {
fs.mkdirSync(configsDir, { recursive: true });
}
// Write tokens to secure file
const jsContent = `// Pre-authenticated tokens for load testing
// Generated: ${new Date().toISOString()}
// Total tokens: ${tokens.length}
// Generation time: ${duration} seconds
//
// ⚠️ SECURITY: This file contains real authentication tokens
// ⚠️ DO NOT COMMIT TO GIT - File is gitignored
export const PRE_AUTHENTICATED_TOKENS = ${JSON.stringify(tokens, null, 2)};
export function getPreAuthenticatedToken(vuId = 1) {
if (PRE_AUTHENTICATED_TOKENS.length === 0) {
throw new Error('No pre-authenticated tokens available');
}
const tokenIndex = (vuId - 1) % PRE_AUTHENTICATED_TOKENS.length;
const tokenData = PRE_AUTHENTICATED_TOKENS[tokenIndex];
return {
access_token: tokenData.token,
user: { email: tokenData.user },
generated: tokenData.generated
};
}
// Generate single session ID for this test run
const LOAD_TEST_SESSION_ID = '${new Date().toISOString().slice(0, 16).replace(/:/g, "-")}-' + Math.random().toString(36).substr(2, 8);
export function getPreAuthenticatedHeaders(vuId = 1) {
const authData = getPreAuthenticatedToken(vuId);
return {
'Content-Type': 'application/json',
'Authorization': \`Bearer \${authData.access_token}\`,
'X-Load-Test-Session': LOAD_TEST_SESSION_ID,
'X-Load-Test-VU': vuId.toString(),
'X-Load-Test-User': authData.user.email,
};
}
export const TOKEN_STATS = {
total: PRE_AUTHENTICATED_TOKENS.length,
users: [...new Set(PRE_AUTHENTICATED_TOKENS.map(t => t.user))].length,
generated: PRE_AUTHENTICATED_TOKENS[0]?.generated || 'unknown'
};
console.log(\`🔐 Loaded \${TOKEN_STATS.total} pre-authenticated tokens from \${TOKEN_STATS.users} users\`);
`;
const tokenFile = path.join(configsDir, "pre-authenticated-tokens.js");
fs.writeFileSync(tokenFile, jsContent);
console.log(`💾 Saved to configs/pre-authenticated-tokens.js`);
console.log(`🚀 Ready for ${tokens.length} concurrent VU load testing!`);
console.log(
`\n🔒 Security Note: Token file is gitignored and will not be committed`,
);
return tokens.length;
}
// Run if called directly
if (process.argv[1] === new URL(import.meta.url).pathname) {
generateTokens().catch(console.error);
}
export { generateTokens };

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@@ -1,611 +0,0 @@
#!/usr/bin/env node
// AutoGPT Platform Load Test Orchestrator
// Runs comprehensive test suite locally or in k6 cloud
// Collects URLs, statistics, and generates reports
const { spawn } = require("child_process");
const fs = require("fs");
const path = require("path");
console.log("🎯 AUTOGPT PLATFORM LOAD TEST ORCHESTRATOR\n");
console.log("===========================================\n");
// Parse command line arguments
const args = process.argv.slice(2);
const environment = args[0] || "DEV"; // LOCAL, DEV, PROD
const executionMode = args[1] || "cloud"; // local, cloud
const testScale = args[2] || "full"; // small, full
console.log(`🌍 Target Environment: ${environment}`);
console.log(`🚀 Execution Mode: ${executionMode}`);
console.log(`📏 Test Scale: ${testScale}`);
// Test scenario definitions
const testScenarios = {
// Small scale for validation (3 tests, ~5 minutes)
small: [
{
name: "Basic_Connectivity_Test",
file: "tests/basic/connectivity-test.js",
vus: 5,
duration: "30s",
},
{
name: "Core_API_Quick_Test",
file: "tests/api/core-api-test.js",
vus: 10,
duration: "1m",
},
{
name: "Marketplace_Quick_Test",
file: "tests/marketplace/public-access-test.js",
vus: 15,
duration: "1m",
},
],
// Full comprehensive test suite (25 tests, ~2 hours)
full: [
// Marketplace Viewing Tests
{
name: "Viewing_Marketplace_Logged_Out_Day1",
file: "tests/marketplace/public-access-test.js",
vus: 106,
duration: "3m",
},
{
name: "Viewing_Marketplace_Logged_Out_VeryHigh",
file: "tests/marketplace/public-access-test.js",
vus: 314,
duration: "3m",
},
{
name: "Viewing_Marketplace_Logged_In_Day1",
file: "tests/marketplace/library-access-test.js",
vus: 53,
duration: "3m",
},
{
name: "Viewing_Marketplace_Logged_In_VeryHigh",
file: "tests/marketplace/library-access-test.js",
vus: 157,
duration: "3m",
},
// Library Management Tests
{
name: "Adding_Agent_to_Library_Day1",
file: "tests/marketplace/library-access-test.js",
vus: 32,
duration: "3m",
},
{
name: "Adding_Agent_to_Library_VeryHigh",
file: "tests/marketplace/library-access-test.js",
vus: 95,
duration: "3m",
},
{
name: "Viewing_Library_Home_0_Agents_Day1",
file: "tests/marketplace/library-access-test.js",
vus: 53,
duration: "3m",
},
{
name: "Viewing_Library_Home_0_Agents_VeryHigh",
file: "tests/marketplace/library-access-test.js",
vus: 157,
duration: "3m",
},
// Core API Tests
{
name: "Core_API_Load_Test",
file: "tests/api/core-api-test.js",
vus: 100,
duration: "3m",
},
{
name: "Graph_Execution_Load_Test",
file: "tests/api/graph-execution-test.js",
vus: 100,
duration: "3m",
},
// Single API Endpoint Tests
{
name: "Credits_API_Single_Endpoint",
file: "tests/basic/single-endpoint-test.js",
vus: 50,
duration: "3m",
env: { ENDPOINT: "credits", CONCURRENT_REQUESTS: 10 },
},
{
name: "Graphs_API_Single_Endpoint",
file: "tests/basic/single-endpoint-test.js",
vus: 50,
duration: "3m",
env: { ENDPOINT: "graphs", CONCURRENT_REQUESTS: 10 },
},
{
name: "Blocks_API_Single_Endpoint",
file: "tests/basic/single-endpoint-test.js",
vus: 50,
duration: "3m",
env: { ENDPOINT: "blocks", CONCURRENT_REQUESTS: 10 },
},
{
name: "Executions_API_Single_Endpoint",
file: "tests/basic/single-endpoint-test.js",
vus: 50,
duration: "3m",
env: { ENDPOINT: "executions", CONCURRENT_REQUESTS: 10 },
},
// Comprehensive Platform Tests
{
name: "Comprehensive_Platform_Low",
file: "tests/comprehensive/platform-journey-test.js",
vus: 25,
duration: "3m",
},
{
name: "Comprehensive_Platform_Medium",
file: "tests/comprehensive/platform-journey-test.js",
vus: 50,
duration: "3m",
},
{
name: "Comprehensive_Platform_High",
file: "tests/comprehensive/platform-journey-test.js",
vus: 100,
duration: "3m",
},
// User Authentication Workflows
{
name: "User_Auth_Workflows_Day1",
file: "tests/basic/connectivity-test.js",
vus: 50,
duration: "3m",
},
{
name: "User_Auth_Workflows_VeryHigh",
file: "tests/basic/connectivity-test.js",
vus: 100,
duration: "3m",
},
// Mixed Load Tests
{
name: "Mixed_Load_Light",
file: "tests/api/core-api-test.js",
vus: 75,
duration: "5m",
},
{
name: "Mixed_Load_Heavy",
file: "tests/marketplace/public-access-test.js",
vus: 200,
duration: "5m",
},
// Stress Tests
{
name: "Marketplace_Stress_Test",
file: "tests/marketplace/public-access-test.js",
vus: 500,
duration: "3m",
},
{
name: "Core_API_Stress_Test",
file: "tests/api/core-api-test.js",
vus: 300,
duration: "3m",
},
// Extended Duration Tests
{
name: "Long_Duration_Marketplace",
file: "tests/marketplace/library-access-test.js",
vus: 100,
duration: "10m",
},
{
name: "Long_Duration_Core_API",
file: "tests/api/core-api-test.js",
vus: 100,
duration: "10m",
},
],
};
const scenarios = testScenarios[testScale];
console.log(`📊 Running ${scenarios.length} test scenarios`);
// Results collection
const results = [];
const cloudUrls = [];
const detailedMetrics = [];
// Create results directory
const timestamp = new Date()
.toISOString()
.replace(/[:.]/g, "-")
.substring(0, 16);
const resultsDir = `results-${environment.toLowerCase()}-${executionMode}-${testScale}-${timestamp}`;
if (!fs.existsSync(resultsDir)) {
fs.mkdirSync(resultsDir);
}
// Function to run a single test
function runTest(scenario, testIndex) {
return new Promise((resolve, reject) => {
console.log(`\n🚀 Test ${testIndex}/${scenarios.length}: ${scenario.name}`);
console.log(
`📊 Config: ${scenario.vus} VUs × ${scenario.duration} (${executionMode} mode)`,
);
console.log(`📁 Script: ${scenario.file}`);
// Build k6 command
let k6Command, k6Args;
// Determine k6 binary location
const isInPod = fs.existsSync("/app/k6-v0.54.0-linux-amd64/k6");
const k6Binary = isInPod ? "/app/k6-v0.54.0-linux-amd64/k6" : "k6";
// Build environment variables
const envVars = [
`K6_ENVIRONMENT=${environment}`,
`VUS=${scenario.vus}`,
`DURATION=${scenario.duration}`,
`RAMP_UP=30s`,
`RAMP_DOWN=30s`,
`THRESHOLD_P95=60000`,
`THRESHOLD_P99=60000`,
];
// Add scenario-specific environment variables
if (scenario.env) {
Object.keys(scenario.env).forEach((key) => {
envVars.push(`${key}=${scenario.env[key]}`);
});
}
// Configure command based on execution mode
if (executionMode === "cloud") {
k6Command = k6Binary;
k6Args = ["cloud", "run", scenario.file];
// Add environment variables as --env flags
envVars.forEach((env) => {
k6Args.push("--env", env);
});
} else {
k6Command = k6Binary;
k6Args = ["run", scenario.file];
// Add local output files
const outputFile = path.join(resultsDir, `${scenario.name}.json`);
const summaryFile = path.join(
resultsDir,
`${scenario.name}_summary.json`,
);
k6Args.push("--out", `json=${outputFile}`);
k6Args.push("--summary-export", summaryFile);
}
const startTime = Date.now();
let testUrl = "";
let stdout = "";
let stderr = "";
console.log(`⏱️ Test started: ${new Date().toISOString()}`);
// Set environment variables for spawned process
const processEnv = { ...process.env };
envVars.forEach((env) => {
const [key, value] = env.split("=");
processEnv[key] = value;
});
const childProcess = spawn(k6Command, k6Args, {
env: processEnv,
stdio: ["ignore", "pipe", "pipe"],
});
// Handle stdout
childProcess.stdout.on("data", (data) => {
const output = data.toString();
stdout += output;
// Extract k6 cloud URL
if (executionMode === "cloud") {
const urlMatch = output.match(/output:\s*(https:\/\/[^\s]+)/);
if (urlMatch) {
testUrl = urlMatch[1];
console.log(`🔗 Test URL: ${testUrl}`);
}
}
// Show progress indicators
if (output.includes("Run [")) {
const progressMatch = output.match(/Run\s+\[\s*(\d+)%\s*\]/);
if (progressMatch) {
process.stdout.write(`\r⏳ Progress: ${progressMatch[1]}%`);
}
}
});
// Handle stderr
childProcess.stderr.on("data", (data) => {
stderr += data.toString();
});
// Handle process completion
childProcess.on("close", (code) => {
const endTime = Date.now();
const duration = Math.round((endTime - startTime) / 1000);
console.log(`\n⏱️ Completed in ${duration}s`);
if (code === 0) {
console.log(`${scenario.name} SUCCESS`);
const result = {
test: scenario.name,
status: "SUCCESS",
duration: `${duration}s`,
vus: scenario.vus,
target_duration: scenario.duration,
url: testUrl || "N/A",
execution_mode: executionMode,
environment: environment,
completed_at: new Date().toISOString(),
};
results.push(result);
if (testUrl) {
cloudUrls.push(`${scenario.name}: ${testUrl}`);
}
// Store detailed output for analysis
detailedMetrics.push({
test: scenario.name,
stdout_lines: stdout.split("\n").length,
stderr_lines: stderr.split("\n").length,
has_url: !!testUrl,
});
resolve(result);
} else {
console.error(`${scenario.name} FAILED (exit code ${code})`);
const result = {
test: scenario.name,
status: "FAILED",
error: `Exit code ${code}`,
duration: `${duration}s`,
vus: scenario.vus,
execution_mode: executionMode,
environment: environment,
completed_at: new Date().toISOString(),
};
results.push(result);
reject(new Error(`Test failed with exit code ${code}`));
}
});
// Handle spawn errors
childProcess.on("error", (error) => {
console.error(`${scenario.name} ERROR:`, error.message);
results.push({
test: scenario.name,
status: "ERROR",
error: error.message,
execution_mode: executionMode,
environment: environment,
});
reject(error);
});
});
}
// Main orchestration function
async function runOrchestrator() {
const estimatedMinutes = scenarios.length * (testScale === "small" ? 2 : 5);
console.log(`\n🎯 Starting ${testScale} test suite on ${environment}`);
console.log(`📈 Estimated time: ~${estimatedMinutes} minutes`);
console.log(`🌩️ Execution: ${executionMode} mode\n`);
const startTime = Date.now();
let successCount = 0;
let failureCount = 0;
// Run tests sequentially
for (let i = 0; i < scenarios.length; i++) {
try {
await runTest(scenarios[i], i + 1);
successCount++;
// Pause between tests (avoid overwhelming k6 cloud API)
if (i < scenarios.length - 1) {
const pauseSeconds = testScale === "small" ? 10 : 30;
console.log(`\n⏸️ Pausing ${pauseSeconds}s before next test...\n`);
await new Promise((resolve) =>
setTimeout(resolve, pauseSeconds * 1000),
);
}
} catch (error) {
failureCount++;
console.log(`💥 Continuing after failure...\n`);
// Brief pause before continuing
if (i < scenarios.length - 1) {
await new Promise((resolve) => setTimeout(resolve, 15000));
}
}
}
const totalTime = Math.round((Date.now() - startTime) / 1000);
await generateReports(successCount, failureCount, totalTime);
}
// Generate comprehensive reports
async function generateReports(successCount, failureCount, totalTime) {
console.log("\n🎉 LOAD TEST ORCHESTRATOR COMPLETE\n");
console.log("===================================\n");
// Summary statistics
const successRate = Math.round((successCount / scenarios.length) * 100);
console.log("📊 EXECUTION SUMMARY:");
console.log(
`✅ Successful tests: ${successCount}/${scenarios.length} (${successRate}%)`,
);
console.log(`❌ Failed tests: ${failureCount}/${scenarios.length}`);
console.log(`⏱️ Total execution time: ${Math.round(totalTime / 60)} minutes`);
console.log(`🌍 Environment: ${environment}`);
console.log(`🚀 Mode: ${executionMode}`);
// Generate CSV report
const csvHeaders =
"Test Name,Status,VUs,Target Duration,Actual Duration,Environment,Mode,Test URL,Error,Completed At";
const csvRows = results.map(
(r) =>
`"${r.test}","${r.status}",${r.vus},"${r.target_duration || "N/A"}","${r.duration || "N/A"}","${r.environment}","${r.execution_mode}","${r.url || "N/A"}","${r.error || "None"}","${r.completed_at || "N/A"}"`,
);
const csvContent = [csvHeaders, ...csvRows].join("\n");
const csvFile = path.join(resultsDir, "orchestrator_results.csv");
fs.writeFileSync(csvFile, csvContent);
console.log(`\n📁 CSV Report: ${csvFile}`);
// Generate cloud URLs file
if (executionMode === "cloud" && cloudUrls.length > 0) {
const urlsContent = [
`# AutoGPT Platform Load Test URLs`,
`# Environment: ${environment}`,
`# Generated: ${new Date().toISOString()}`,
`# Dashboard: https://significantgravitas.grafana.net/a/k6-app/`,
"",
...cloudUrls,
"",
"# Direct Dashboard Access:",
"https://significantgravitas.grafana.net/a/k6-app/",
].join("\n");
const urlsFile = path.join(resultsDir, "cloud_test_urls.txt");
fs.writeFileSync(urlsFile, urlsContent);
console.log(`📁 Cloud URLs: ${urlsFile}`);
}
// Generate detailed JSON report
const jsonReport = {
meta: {
orchestrator_version: "1.0",
environment: environment,
execution_mode: executionMode,
test_scale: testScale,
total_scenarios: scenarios.length,
generated_at: new Date().toISOString(),
results_directory: resultsDir,
},
summary: {
successful_tests: successCount,
failed_tests: failureCount,
success_rate: `${successRate}%`,
total_execution_time_seconds: totalTime,
total_execution_time_minutes: Math.round(totalTime / 60),
},
test_results: results,
detailed_metrics: detailedMetrics,
cloud_urls: cloudUrls,
};
const jsonFile = path.join(resultsDir, "orchestrator_results.json");
fs.writeFileSync(jsonFile, JSON.stringify(jsonReport, null, 2));
console.log(`📁 JSON Report: ${jsonFile}`);
// Display immediate results
if (executionMode === "cloud" && cloudUrls.length > 0) {
console.log("\n🔗 K6 CLOUD TEST DASHBOARD URLS:");
console.log("================================");
cloudUrls.slice(0, 5).forEach((url) => console.log(url));
if (cloudUrls.length > 5) {
console.log(`... and ${cloudUrls.length - 5} more URLs in ${urlsFile}`);
}
console.log(
"\n📈 Main Dashboard: https://significantgravitas.grafana.net/a/k6-app/",
);
}
console.log(`\n📂 All results saved in: ${resultsDir}/`);
console.log("🏁 Load Test Orchestrator finished successfully!");
}
// Show usage help
function showUsage() {
console.log("🎯 AutoGPT Platform Load Test Orchestrator\n");
console.log(
"Usage: node load-test-orchestrator.js [ENVIRONMENT] [MODE] [SCALE]\n",
);
console.log("ENVIRONMENT:");
console.log(" LOCAL - http://localhost:8006 (local development)");
console.log(" DEV - https://dev-api.agpt.co (development server)");
console.log(
" PROD - https://api.agpt.co (production - coordinate with team!)\n",
);
console.log("MODE:");
console.log(" local - Run locally with JSON output files");
console.log(" cloud - Run in k6 cloud with dashboard monitoring\n");
console.log("SCALE:");
console.log(" small - 3 validation tests (~5 minutes)");
console.log(" full - 25 comprehensive tests (~2 hours)\n");
console.log("Examples:");
console.log(" node load-test-orchestrator.js DEV cloud small");
console.log(" node load-test-orchestrator.js LOCAL local small");
console.log(" node load-test-orchestrator.js DEV cloud full");
console.log(
" node load-test-orchestrator.js PROD cloud full # Coordinate with team!\n",
);
console.log("Requirements:");
console.log(
" - Pre-authenticated tokens generated (node generate-tokens.js)",
);
console.log(" - k6 installed locally or run from Kubernetes pod");
console.log(" - For cloud mode: K6_CLOUD_TOKEN and K6_CLOUD_PROJECT_ID set");
}
// Handle command line help
if (args.includes("--help") || args.includes("-h")) {
showUsage();
process.exit(0);
}
// Handle graceful shutdown
process.on("SIGINT", () => {
console.log("\n🛑 Orchestrator interrupted by user");
console.log("📊 Generating partial results...");
generateReports(
results.filter((r) => r.status === "SUCCESS").length,
results.filter((r) => r.status === "FAILED").length,
0,
).then(() => {
console.log("🏃‍♂️ Partial results saved");
process.exit(0);
});
});
// Start orchestrator
if (require.main === module) {
runOrchestrator().catch((error) => {
console.error("💥 Orchestrator failed:", error);
process.exit(1);
});
}
module.exports = { runOrchestrator, testScenarios };

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@@ -1,268 +0,0 @@
#!/usr/bin/env node
/**
* Unified Load Test Runner
*
* Supports both local execution and k6 cloud execution with the same interface.
* Automatically detects cloud credentials and provides seamless switching.
*
* Usage:
* node run-tests.js verify # Quick verification (1 VU, 10s)
* node run-tests.js run core-api-test DEV # Run specific test locally
* node run-tests.js run all DEV # Run all tests locally
* node run-tests.js cloud core-api DEV # Run specific test in k6 cloud
* node run-tests.js cloud all DEV # Run all tests in k6 cloud
*/
import { execSync } from "child_process";
import fs from "fs";
const TESTS = {
"connectivity-test": {
script: "tests/basic/connectivity-test.js",
description: "Basic connectivity validation",
cloudConfig: { vus: 10, duration: "2m" },
},
"single-endpoint-test": {
script: "tests/basic/single-endpoint-test.js",
description: "Individual API endpoint testing",
cloudConfig: { vus: 25, duration: "3m" },
},
"core-api-test": {
script: "tests/api/core-api-test.js",
description: "Core API endpoints performance test",
cloudConfig: { vus: 100, duration: "5m" },
},
"graph-execution-test": {
script: "tests/api/graph-execution-test.js",
description: "Graph creation and execution pipeline test",
cloudConfig: { vus: 80, duration: "5m" },
},
"marketplace-public-test": {
script: "tests/marketplace/public-access-test.js",
description: "Public marketplace browsing test",
cloudConfig: { vus: 150, duration: "3m" },
},
"marketplace-library-test": {
script: "tests/marketplace/library-access-test.js",
description: "Authenticated marketplace/library test",
cloudConfig: { vus: 100, duration: "4m" },
},
"comprehensive-test": {
script: "tests/comprehensive/platform-journey-test.js",
description: "Complete user journey simulation",
cloudConfig: { vus: 50, duration: "6m" },
},
};
function checkCloudCredentials() {
const token = process.env.K6_CLOUD_TOKEN;
const projectId = process.env.K6_CLOUD_PROJECT_ID;
if (!token || !projectId) {
console.log("❌ Missing k6 cloud credentials");
console.log("Set: K6_CLOUD_TOKEN and K6_CLOUD_PROJECT_ID");
return false;
}
return true;
}
function verifySetup() {
console.log("🔍 Quick Setup Verification");
// Check tokens
if (!fs.existsSync("configs/pre-authenticated-tokens.js")) {
console.log("❌ No tokens found. Run: node generate-tokens.js");
return false;
}
// Quick test
try {
execSync(
"K6_ENVIRONMENT=DEV VUS=1 DURATION=10s k6 run tests/basic/connectivity-test.js --quiet",
{ stdio: "inherit", cwd: process.cwd() },
);
console.log("✅ Verification successful");
return true;
} catch (error) {
console.log("❌ Verification failed");
return false;
}
}
function runLocalTest(testName, environment) {
const test = TESTS[testName];
if (!test) {
console.log(`❌ Unknown test: ${testName}`);
console.log("Available tests:", Object.keys(TESTS).join(", "));
return;
}
console.log(`🚀 Running ${test.description} locally on ${environment}`);
try {
const cmd = `K6_ENVIRONMENT=${environment} VUS=5 DURATION=30s k6 run ${test.script}`;
execSync(cmd, { stdio: "inherit", cwd: process.cwd() });
console.log("✅ Test completed");
} catch (error) {
console.log("❌ Test failed");
}
}
function runCloudTest(testName, environment) {
const test = TESTS[testName];
if (!test) {
console.log(`❌ Unknown test: ${testName}`);
console.log("Available tests:", Object.keys(TESTS).join(", "));
return;
}
const { vus, duration } = test.cloudConfig;
console.log(`☁️ Running ${test.description} in k6 cloud`);
console.log(` Environment: ${environment}`);
console.log(` Config: ${vus} VUs × ${duration}`);
try {
const cmd = `k6 cloud run --env K6_ENVIRONMENT=${environment} --env VUS=${vus} --env DURATION=${duration} --env RAMP_UP=30s --env RAMP_DOWN=30s ${test.script}`;
const output = execSync(cmd, {
stdio: "pipe",
cwd: process.cwd(),
encoding: "utf8",
});
// Extract and display URL
const urlMatch = output.match(/https:\/\/[^\s]*grafana[^\s]*/);
if (urlMatch) {
const url = urlMatch[0];
console.log(`🔗 Test URL: ${url}`);
// Save to results file
const timestamp = new Date().toISOString();
const result = `${timestamp} - ${testName}: ${url}\n`;
fs.appendFileSync("k6-cloud-results.txt", result);
}
console.log("✅ Cloud test started successfully");
} catch (error) {
console.log("❌ Cloud test failed to start");
console.log(error.message);
}
}
function runAllLocalTests(environment) {
console.log(`🚀 Running all tests locally on ${environment}`);
for (const [testName, test] of Object.entries(TESTS)) {
console.log(`\n📊 ${test.description}`);
runLocalTest(testName, environment);
}
}
function runAllCloudTests(environment) {
console.log(`☁️ Running all tests in k6 cloud on ${environment}`);
const testNames = Object.keys(TESTS);
for (let i = 0; i < testNames.length; i++) {
const testName = testNames[i];
console.log(`\n📊 Test ${i + 1}/${testNames.length}: ${testName}`);
runCloudTest(testName, environment);
// Brief pause between cloud tests (except last one)
if (i < testNames.length - 1) {
console.log("⏸️ Waiting 2 minutes before next cloud test...");
execSync("sleep 120");
}
}
}
function listTests() {
console.log("📋 Available Tests:");
console.log("==================");
Object.entries(TESTS).forEach(([name, test]) => {
const { vus, duration } = test.cloudConfig;
console.log(` ${name.padEnd(20)} - ${test.description}`);
console.log(` ${" ".repeat(20)} Cloud: ${vus} VUs × ${duration}`);
});
console.log("\n🌍 Available Environments: LOCAL, DEV, PROD");
console.log("\n💡 Examples:");
console.log(" # Local execution (5 VUs, 30s)");
console.log(" node run-tests.js verify");
console.log(" node run-tests.js run core-api-test DEV");
console.log(" node run-tests.js run core-api-test,marketplace-test DEV");
console.log(" node run-tests.js run all DEV");
console.log("");
console.log(" # Cloud execution (high VUs, longer duration)");
console.log(" node run-tests.js cloud core-api DEV");
console.log(" node run-tests.js cloud all DEV");
const hasCloudCreds = checkCloudCredentials();
console.log(
`\n☁️ Cloud Status: ${hasCloudCreds ? "✅ Configured" : "❌ Missing credentials"}`,
);
}
function runSequentialTests(testNames, environment, isCloud = false) {
const tests = testNames.split(",").map((t) => t.trim());
const mode = isCloud ? "cloud" : "local";
console.log(
`🚀 Running ${tests.length} tests sequentially in ${mode} mode on ${environment}`,
);
for (let i = 0; i < tests.length; i++) {
const testName = tests[i];
console.log(`\n📊 Test ${i + 1}/${tests.length}: ${testName}`);
if (isCloud) {
runCloudTest(testName, environment);
} else {
runLocalTest(testName, environment);
}
// Brief pause between tests (except last one)
if (i < tests.length - 1) {
const pauseTime = isCloud ? "2 minutes" : "10 seconds";
const pauseCmd = isCloud ? "sleep 120" : "sleep 10";
console.log(`⏸️ Waiting ${pauseTime} before next test...`);
if (!isCloud) {
// Note: In real implementation, would use setTimeout/sleep for local tests
}
}
}
}
// Main CLI
const [, , command, testOrEnv, environment] = process.argv;
switch (command) {
case "verify":
verifySetup();
break;
case "list":
listTests();
break;
case "run":
if (testOrEnv === "all") {
runAllLocalTests(environment || "DEV");
} else if (testOrEnv?.includes(",")) {
runSequentialTests(testOrEnv, environment || "DEV", false);
} else {
runLocalTest(testOrEnv, environment || "DEV");
}
break;
case "cloud":
if (!checkCloudCredentials()) {
process.exit(1);
}
if (testOrEnv === "all") {
runAllCloudTests(environment || "DEV");
} else if (testOrEnv?.includes(",")) {
runSequentialTests(testOrEnv, environment || "DEV", true);
} else {
runCloudTest(testOrEnv, environment || "DEV");
}
break;
default:
listTests();
}

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@@ -1,197 +0,0 @@
// Simple API diagnostic test
import http from "k6/http";
import { check } from "k6";
import { getEnvironmentConfig } from "../../configs/environment.js";
import { getPreAuthenticatedHeaders } from "../../configs/pre-authenticated-tokens.js";
const config = getEnvironmentConfig();
export const options = {
stages: [
{ duration: __ENV.RAMP_UP || "1m", target: parseInt(__ENV.VUS) || 1 },
{ duration: __ENV.DURATION || "5m", target: parseInt(__ENV.VUS) || 1 },
{ duration: __ENV.RAMP_DOWN || "1m", target: 0 },
],
// Thresholds disabled to prevent test abortion - collect all performance data
// thresholds: {
// checks: ['rate>0.70'],
// http_req_duration: ['p(95)<30000'],
// http_req_failed: ['rate<0.3'],
// },
cloud: {
projectID: __ENV.K6_CLOUD_PROJECT_ID,
name: "AutoGPT Platform - Core API Validation Test",
},
// Timeout configurations to prevent early termination
setupTimeout: "60s",
teardownTimeout: "60s",
noConnectionReuse: false,
userAgent: "k6-load-test/1.0",
};
export default function () {
// Get load multiplier - how many concurrent requests each VU should make
const requestsPerVU = parseInt(__ENV.REQUESTS_PER_VU) || 1;
try {
// Step 1: Get pre-authenticated headers (no auth API calls during test)
const headers = getPreAuthenticatedHeaders(__VU);
// Handle missing token gracefully
if (!headers || !headers.Authorization) {
console.log(
`⚠️ VU ${__VU} has no valid pre-authenticated token - skipping core API test`,
);
check(null, {
"Core API: Failed gracefully without crashing VU": () => true,
});
return; // Exit iteration gracefully without crashing
}
console.log(
`🚀 VU ${__VU} making ${requestsPerVU} concurrent API requests...`,
);
// Create array of API requests to run concurrently
const requests = [];
for (let i = 0; i < requestsPerVU; i++) {
// Add core API requests that represent realistic user workflows
requests.push({
method: "GET",
url: `${config.API_BASE_URL}/api/credits`,
params: { headers },
});
requests.push({
method: "GET",
url: `${config.API_BASE_URL}/api/graphs`,
params: { headers },
});
requests.push({
method: "GET",
url: `${config.API_BASE_URL}/api/blocks`,
params: { headers },
});
}
// Execute all requests concurrently
const responses = http.batch(requests);
// Validate results
let creditsSuccesses = 0;
let graphsSuccesses = 0;
let blocksSuccesses = 0;
for (let i = 0; i < responses.length; i++) {
const response = responses[i];
const apiType = i % 3; // 0=credits, 1=graphs, 2=blocks
if (apiType === 0) {
// Credits API request
check(response, {
"Credits API: HTTP Status is 200": (r) => r.status === 200,
"Credits API: Not Auth Error (401/403)": (r) =>
r.status !== 401 && r.status !== 403,
"Credits API: Response has valid JSON": (r) => {
try {
JSON.parse(r.body);
return true;
} catch (e) {
return false;
}
},
"Credits API: Response has credits field": (r) => {
try {
const data = JSON.parse(r.body);
return data && typeof data.credits === "number";
} catch (e) {
return false;
}
},
"Credits API: Overall Success": (r) => {
try {
if (r.status !== 200) return false;
const data = JSON.parse(r.body);
return data && typeof data.credits === "number";
} catch (e) {
return false;
}
},
});
} else if (apiType === 1) {
// Graphs API request
check(response, {
"Graphs API: HTTP Status is 200": (r) => r.status === 200,
"Graphs API: Not Auth Error (401/403)": (r) =>
r.status !== 401 && r.status !== 403,
"Graphs API: Response has valid JSON": (r) => {
try {
JSON.parse(r.body);
return true;
} catch (e) {
return false;
}
},
"Graphs API: Response is array": (r) => {
try {
const data = JSON.parse(r.body);
return Array.isArray(data);
} catch (e) {
return false;
}
},
"Graphs API: Overall Success": (r) => {
try {
if (r.status !== 200) return false;
const data = JSON.parse(r.body);
return Array.isArray(data);
} catch (e) {
return false;
}
},
});
} else {
// Blocks API request
check(response, {
"Blocks API: HTTP Status is 200": (r) => r.status === 200,
"Blocks API: Not Auth Error (401/403)": (r) =>
r.status !== 401 && r.status !== 403,
"Blocks API: Response has valid JSON": (r) => {
try {
JSON.parse(r.body);
return true;
} catch (e) {
return false;
}
},
"Blocks API: Response has blocks data": (r) => {
try {
const data = JSON.parse(r.body);
return data && (Array.isArray(data) || typeof data === "object");
} catch (e) {
return false;
}
},
"Blocks API: Overall Success": (r) => {
try {
if (r.status !== 200) return false;
const data = JSON.parse(r.body);
return data && (Array.isArray(data) || typeof data === "object");
} catch (e) {
return false;
}
},
});
}
}
console.log(
`✅ VU ${__VU} completed ${responses.length} API requests with detailed auth/validation tracking`,
);
} catch (error) {
console.error(`💥 Test failed: ${error.message}`);
console.error(`💥 Stack: ${error.stack}`);
}
}

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@@ -1,249 +0,0 @@
// Dedicated graph execution load testing
import http from "k6/http";
import { check, sleep, group } from "k6";
import { Rate, Trend, Counter } from "k6/metrics";
import { getEnvironmentConfig } from "../../configs/environment.js";
import { getPreAuthenticatedHeaders } from "../../configs/pre-authenticated-tokens.js";
// Test data generation functions
function generateTestGraph(name = null) {
const graphName =
name || `Load Test Graph ${Math.random().toString(36).substr(2, 9)}`;
return {
name: graphName,
description: "Generated graph for load testing purposes",
graph: {
name: graphName,
description: "Load testing graph",
nodes: [
{
id: "input_node",
name: "Agent Input",
block_id: "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b",
input_default: {
name: "Load Test Input",
description: "Test input for load testing",
placeholder_values: {},
},
input_nodes: [],
output_nodes: ["output_node"],
metadata: { position: { x: 100, y: 100 } },
},
{
id: "output_node",
name: "Agent Output",
block_id: "363ae599-353e-4804-937e-b2ee3cef3da4",
input_default: {
name: "Load Test Output",
description: "Test output for load testing",
value: "Test output value",
},
input_nodes: ["input_node"],
output_nodes: [],
metadata: { position: { x: 300, y: 100 } },
},
],
links: [
{
source_id: "input_node",
sink_id: "output_node",
source_name: "result",
sink_name: "value",
},
],
},
};
}
function generateExecutionInputs() {
return {
"Load Test Input": {
name: "Load Test Input",
description: "Test input for load testing",
placeholder_values: {
test_data: `Test execution at ${new Date().toISOString()}`,
test_parameter: Math.random().toString(36).substr(2, 9),
numeric_value: Math.floor(Math.random() * 1000),
},
},
};
}
const config = getEnvironmentConfig();
// Custom metrics for graph execution testing
const graphCreations = new Counter("graph_creations_total");
const graphExecutions = new Counter("graph_executions_total");
const graphExecutionTime = new Trend("graph_execution_duration");
const graphCreationTime = new Trend("graph_creation_duration");
const executionErrors = new Rate("execution_errors");
// Configurable options for easy load adjustment
export const options = {
stages: [
{ duration: __ENV.RAMP_UP || "1m", target: parseInt(__ENV.VUS) || 5 },
{ duration: __ENV.DURATION || "5m", target: parseInt(__ENV.VUS) || 5 },
{ duration: __ENV.RAMP_DOWN || "1m", target: 0 },
],
// Thresholds disabled to prevent test abortion - collect all performance data
// thresholds: {
// checks: ['rate>0.60'],
// http_req_duration: ['p(95)<45000', 'p(99)<60000'],
// http_req_failed: ['rate<0.4'],
// graph_execution_duration: ['p(95)<45000'],
// graph_creation_duration: ['p(95)<30000'],
// },
cloud: {
projectID: __ENV.K6_CLOUD_PROJECT_ID,
name: "AutoGPT Platform - Graph Creation & Execution Test",
},
// Timeout configurations to prevent early termination
setupTimeout: "60s",
teardownTimeout: "60s",
noConnectionReuse: false,
userAgent: "k6-load-test/1.0",
};
export function setup() {
console.log("🎯 Setting up graph execution load test...");
console.log(
`Configuration: VUs=${parseInt(__ENV.VUS) || 5}, Duration=${__ENV.DURATION || "2m"}`,
);
return {
timestamp: Date.now(),
};
}
export default function (data) {
// Get load multiplier - how many concurrent operations each VU should perform
const requestsPerVU = parseInt(__ENV.REQUESTS_PER_VU) || 1;
// Get pre-authenticated headers (no auth API calls during test)
const headers = getPreAuthenticatedHeaders(__VU);
// Handle missing token gracefully
if (!headers || !headers.Authorization) {
console.log(
`⚠️ VU ${__VU} has no valid pre-authenticated token - skipping graph execution`,
);
check(null, {
"Graph Execution: Failed gracefully without crashing VU": () => true,
});
return; // Exit iteration gracefully without crashing
}
console.log(
`🚀 VU ${__VU} performing ${requestsPerVU} concurrent graph operations...`,
);
// Create requests for concurrent execution
const graphRequests = [];
for (let i = 0; i < requestsPerVU; i++) {
// Generate graph data
const graphData = generateTestGraph();
// Add graph creation request
graphRequests.push({
method: "POST",
url: `${config.API_BASE_URL}/api/graphs`,
body: JSON.stringify(graphData),
params: { headers },
});
}
// Execute all graph creations concurrently
console.log(`📊 Creating ${requestsPerVU} graphs concurrently...`);
const responses = http.batch(graphRequests);
// Process results
let successCount = 0;
const createdGraphs = [];
for (let i = 0; i < responses.length; i++) {
const response = responses[i];
const success = check(response, {
[`Graph ${i + 1} created successfully`]: (r) => r.status === 200,
});
if (success && response.status === 200) {
successCount++;
try {
const graph = JSON.parse(response.body);
createdGraphs.push(graph);
graphCreations.add(1);
} catch (e) {
console.error(`Error parsing graph ${i + 1} response:`, e);
}
} else {
console.log(`❌ Graph ${i + 1} creation failed: ${response.status}`);
}
}
console.log(
`✅ VU ${__VU} created ${successCount}/${requestsPerVU} graphs concurrently`,
);
// Execute a subset of created graphs (to avoid overloading execution)
const graphsToExecute = createdGraphs.slice(
0,
Math.min(5, createdGraphs.length),
);
if (graphsToExecute.length > 0) {
console.log(`⚡ Executing ${graphsToExecute.length} graphs...`);
const executionRequests = [];
for (const graph of graphsToExecute) {
const executionInputs = generateExecutionInputs();
executionRequests.push({
method: "POST",
url: `${config.API_BASE_URL}/api/graphs/${graph.id}/execute/${graph.version}`,
body: JSON.stringify({
inputs: executionInputs,
credentials_inputs: {},
}),
params: { headers },
});
}
// Execute graphs concurrently
const executionResponses = http.batch(executionRequests);
let executionSuccessCount = 0;
for (let i = 0; i < executionResponses.length; i++) {
const response = executionResponses[i];
const success = check(response, {
[`Graph ${i + 1} execution initiated`]: (r) =>
r.status === 200 || r.status === 402,
});
if (success) {
executionSuccessCount++;
graphExecutions.add(1);
}
}
console.log(
`✅ VU ${__VU} executed ${executionSuccessCount}/${graphsToExecute.length} graphs`,
);
}
// Think time between iterations
sleep(Math.random() * 2 + 1); // 1-3 seconds
}
// Legacy functions removed - replaced by concurrent execution in main function
// These functions are no longer used since implementing http.batch() for true concurrency
export function teardown(data) {
console.log("🧹 Cleaning up graph execution load test...");
console.log(`Total graph creations: ${graphCreations.value || 0}`);
console.log(`Total graph executions: ${graphExecutions.value || 0}`);
const testDuration = Date.now() - data.timestamp;
console.log(`Test completed in ${testDuration}ms`);
}

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@@ -1,137 +0,0 @@
/**
* Basic Connectivity Test
*
* Tests basic connectivity and authentication without requiring backend API access
* This test validates that the core infrastructure is working correctly
*/
import http from "k6/http";
import { check } from "k6";
import { getEnvironmentConfig } from "../../configs/environment.js";
import { getPreAuthenticatedHeaders } from "../../configs/pre-authenticated-tokens.js";
const config = getEnvironmentConfig();
export const options = {
stages: [
{ duration: __ENV.RAMP_UP || "1m", target: parseInt(__ENV.VUS) || 1 },
{ duration: __ENV.DURATION || "5m", target: parseInt(__ENV.VUS) || 1 },
{ duration: __ENV.RAMP_DOWN || "1m", target: 0 },
],
thresholds: {
checks: ["rate>0.70"], // Reduced from 0.85 due to auth timeouts under load
http_req_duration: ["p(95)<30000"], // Increased for cloud testing with high concurrency
http_req_failed: ["rate<0.6"], // Increased to account for auth timeouts
},
cloud: {
projectID: __ENV.K6_CLOUD_PROJECT_ID,
name: "AutoGPT Platform - Basic Connectivity & Auth Test",
},
// Timeout configurations to prevent early termination
setupTimeout: "60s",
teardownTimeout: "60s",
noConnectionReuse: false,
userAgent: "k6-load-test/1.0",
};
export default function () {
// Get load multiplier - how many concurrent requests each VU should make
const requestsPerVU = parseInt(__ENV.REQUESTS_PER_VU) || 1;
try {
// Get pre-authenticated headers
const headers = getPreAuthenticatedHeaders(__VU);
// Handle authentication failure gracefully
if (!headers || !headers.Authorization) {
console.log(
`⚠️ VU ${__VU} has no valid pre-authentication token - skipping iteration`,
);
check(null, {
"Authentication: Failed gracefully without crashing VU": () => true,
});
return; // Exit iteration gracefully without crashing
}
console.log(`🚀 VU ${__VU} making ${requestsPerVU} concurrent requests...`);
// Create array of request functions to run concurrently
const requests = [];
for (let i = 0; i < requestsPerVU; i++) {
requests.push({
method: "GET",
url: `${config.SUPABASE_URL}/rest/v1/`,
params: { headers: { apikey: config.SUPABASE_ANON_KEY } },
});
requests.push({
method: "GET",
url: `${config.API_BASE_URL}/health`,
params: { headers },
});
}
// Execute all requests concurrently
const responses = http.batch(requests);
// Validate results
let supabaseSuccesses = 0;
let backendSuccesses = 0;
for (let i = 0; i < responses.length; i++) {
const response = responses[i];
if (i % 2 === 0) {
// Supabase request
const connectivityCheck = check(response, {
"Supabase connectivity: Status is not 500": (r) => r.status !== 500,
"Supabase connectivity: Response time < 5s": (r) =>
r.timings.duration < 5000,
});
if (connectivityCheck) supabaseSuccesses++;
} else {
// Backend request
const backendCheck = check(response, {
"Backend server: Responds (any status)": (r) => r.status > 0,
"Backend server: Response time < 5s": (r) =>
r.timings.duration < 5000,
});
if (backendCheck) backendSuccesses++;
}
}
console.log(
`✅ VU ${__VU} completed: ${supabaseSuccesses}/${requestsPerVU} Supabase, ${backendSuccesses}/${requestsPerVU} backend requests successful`,
);
// Basic auth validation (once per iteration)
const authCheck = check(headers, {
"Authentication: Pre-auth token available": (h) =>
h && h.Authorization && h.Authorization.length > 0,
});
// JWT structure validation (once per iteration)
const token = headers.Authorization.replace("Bearer ", "");
const tokenParts = token.split(".");
const tokenStructureCheck = check(tokenParts, {
"JWT token: Has 3 parts (header.payload.signature)": (parts) =>
parts.length === 3,
"JWT token: Header is base64": (parts) =>
parts[0] && parts[0].length > 10,
"JWT token: Payload is base64": (parts) =>
parts[1] && parts[1].length > 50,
"JWT token: Signature exists": (parts) =>
parts[2] && parts[2].length > 10,
});
} catch (error) {
console.error(`💥 Test failed: ${error.message}`);
check(null, {
"Test execution: No errors": () => false,
});
}
}
export function teardown(data) {
console.log(`🏁 Basic connectivity test completed`);
}

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@@ -1,104 +0,0 @@
// Test individual API endpoints to isolate performance bottlenecks
import http from "k6/http";
import { check } from "k6";
import { getEnvironmentConfig } from "../../configs/environment.js";
import { getPreAuthenticatedHeaders } from "../../configs/pre-authenticated-tokens.js";
const config = getEnvironmentConfig();
export const options = {
stages: [
{ duration: __ENV.RAMP_UP || "10s", target: parseInt(__ENV.VUS) || 3 },
{ duration: __ENV.DURATION || "20s", target: parseInt(__ENV.VUS) || 3 },
{ duration: __ENV.RAMP_DOWN || "10s", target: 0 },
],
thresholds: {
checks: ["rate>0.50"], // 50% success rate (was 70%)
http_req_duration: ["p(95)<60000"], // P95 under 60s (was 5s)
http_req_failed: ["rate<0.5"], // 50% failure rate allowed (was 30%)
},
cloud: {
projectID: parseInt(__ENV.K6_CLOUD_PROJECT_ID) || 4254406,
name: `AutoGPT Single Endpoint Test - ${__ENV.ENDPOINT || "credits"} API`,
},
};
export default function () {
const endpoint = __ENV.ENDPOINT || "credits"; // credits, graphs, blocks, executions
const concurrentRequests = parseInt(__ENV.CONCURRENT_REQUESTS) || 1;
try {
const headers = getPreAuthenticatedHeaders(__VU);
if (!headers || !headers.Authorization) {
console.log(
`⚠️ VU ${__VU} has no valid pre-authentication token - skipping test`,
);
return;
}
console.log(
`🚀 VU ${__VU} testing /api/${endpoint} with ${concurrentRequests} concurrent requests`,
);
if (concurrentRequests === 1) {
// Single request mode (original behavior)
const response = http.get(`${config.API_BASE_URL}/api/${endpoint}`, {
headers,
});
const success = check(response, {
[`${endpoint} API: Status is 200`]: (r) => r.status === 200,
[`${endpoint} API: Response time < 3s`]: (r) =>
r.timings.duration < 3000,
});
if (success) {
console.log(
`✅ VU ${__VU} /api/${endpoint} successful: ${response.timings.duration}ms`,
);
} else {
console.log(
`❌ VU ${__VU} /api/${endpoint} failed: ${response.status}, ${response.timings.duration}ms`,
);
}
} else {
// Concurrent requests mode using http.batch()
const requests = [];
for (let i = 0; i < concurrentRequests; i++) {
requests.push({
method: "GET",
url: `${config.API_BASE_URL}/api/${endpoint}`,
params: { headers },
});
}
const responses = http.batch(requests);
let successCount = 0;
let totalTime = 0;
for (let i = 0; i < responses.length; i++) {
const response = responses[i];
const success = check(response, {
[`${endpoint} API Request ${i + 1}: Status is 200`]: (r) =>
r.status === 200,
[`${endpoint} API Request ${i + 1}: Response time < 5s`]: (r) =>
r.timings.duration < 5000,
});
if (success) {
successCount++;
}
totalTime += response.timings.duration;
}
const avgTime = totalTime / responses.length;
console.log(
`✅ VU ${__VU} /api/${endpoint}: ${successCount}/${concurrentRequests} successful, avg: ${avgTime.toFixed(0)}ms`,
);
}
} catch (error) {
console.error(`💥 VU ${__VU} error: ${error.message}`);
}
}

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@@ -1,508 +0,0 @@
import http from "k6/http";
import { check, sleep, group } from "k6";
import { Rate, Trend, Counter } from "k6/metrics";
import {
getEnvironmentConfig,
PERFORMANCE_CONFIG,
} from "../../configs/environment.js";
import { getPreAuthenticatedHeaders } from "../../configs/pre-authenticated-tokens.js";
// Inline test data generators (simplified from utils/test-data.js)
function generateTestGraph(name = null) {
const graphName =
name || `Load Test Graph ${Math.random().toString(36).substr(2, 9)}`;
return {
name: graphName,
description: "Generated graph for load testing purposes",
graph: {
nodes: [],
links: [],
},
};
}
function generateExecutionInputs() {
return { test_input: "load_test_value" };
}
function generateScheduleData() {
return { enabled: false };
}
function generateAPIKeyRequest() {
return { name: "Load Test API Key" };
}
const config = getEnvironmentConfig();
// Custom metrics
const userOperations = new Counter("user_operations_total");
const graphOperations = new Counter("graph_operations_total");
const executionOperations = new Counter("execution_operations_total");
const apiResponseTime = new Trend("api_response_time");
const authErrors = new Rate("auth_errors");
// Test configuration for normal load testing
export const options = {
stages: [
{
duration: __ENV.RAMP_UP || "1m",
target: parseInt(__ENV.VUS) || PERFORMANCE_CONFIG.DEFAULT_VUS,
},
{
duration: __ENV.DURATION || "5m",
target: parseInt(__ENV.VUS) || PERFORMANCE_CONFIG.DEFAULT_VUS,
},
{ duration: __ENV.RAMP_DOWN || "1m", target: 0 },
],
// maxDuration: '15m', // Removed - not supported in k6 cloud
thresholds: {
checks: ["rate>0.50"], // Reduced for high concurrency complex operations
http_req_duration: ["p(95)<60000", "p(99)<60000"], // Allow up to 60s response times
http_req_failed: ["rate<0.5"], // Allow 50% failure rate for stress testing
},
cloud: {
projectID: __ENV.K6_CLOUD_PROJECT_ID,
name: "AutoGPT Platform - Full Platform Integration Test",
},
// Timeout configurations to prevent early termination
setupTimeout: "60s",
teardownTimeout: "60s",
noConnectionReuse: false,
userAgent: "k6-load-test/1.0",
};
export function setup() {
console.log("🎯 Setting up load test scenario...");
return {
timestamp: Date.now(),
};
}
export default function (data) {
// Get load multiplier - how many concurrent user journeys each VU should simulate
const requestsPerVU = parseInt(__ENV.REQUESTS_PER_VU) || 1;
let headers;
try {
headers = getPreAuthenticatedHeaders(__VU);
} catch (error) {
console.error(`❌ Authentication failed:`, error);
authErrors.add(1);
return;
}
// Handle authentication failure gracefully
if (!headers || !headers.Authorization) {
console.log(
`⚠️ VU ${__VU} has no valid pre-authentication token - skipping comprehensive platform test`,
);
check(null, {
"Comprehensive Platform: Failed gracefully without crashing VU": () =>
true,
});
return; // Exit iteration gracefully without crashing
}
console.log(
`🚀 VU ${__VU} simulating ${requestsPerVU} realistic user workflows...`,
);
// Create concurrent requests for all user journeys
const requests = [];
// Simulate realistic user workflows instead of just API hammering
for (let i = 0; i < requestsPerVU; i++) {
// Workflow 1: User checking their dashboard
requests.push({
method: "GET",
url: `${config.API_BASE_URL}/api/credits`,
params: { headers },
});
requests.push({
method: "GET",
url: `${config.API_BASE_URL}/api/graphs`,
params: { headers },
});
// Workflow 2: User exploring available blocks for building agents
requests.push({
method: "GET",
url: `${config.API_BASE_URL}/api/blocks`,
params: { headers },
});
// Workflow 3: User monitoring their recent executions
requests.push({
method: "GET",
url: `${config.API_BASE_URL}/api/executions`,
params: { headers },
});
}
console.log(
`📊 Executing ${requests.length} requests across realistic user workflows...`,
);
// Execute all requests concurrently
const responses = http.batch(requests);
// Process results and count successes
let creditsSuccesses = 0,
graphsSuccesses = 0,
blocksSuccesses = 0,
executionsSuccesses = 0;
for (let i = 0; i < responses.length; i++) {
const response = responses[i];
const operationType = i % 4; // Each set of 4 requests: 0=credits, 1=graphs, 2=blocks, 3=executions
switch (operationType) {
case 0: // Dashboard: Check credits
if (
check(response, {
"Dashboard: User credits loaded successfully": (r) =>
r.status === 200,
})
) {
creditsSuccesses++;
userOperations.add(1);
}
break;
case 1: // Dashboard: View graphs
if (
check(response, {
"Dashboard: User graphs loaded successfully": (r) =>
r.status === 200,
})
) {
graphsSuccesses++;
graphOperations.add(1);
}
break;
case 2: // Exploration: Browse available blocks
if (
check(response, {
"Block Explorer: Available blocks loaded successfully": (r) =>
r.status === 200,
})
) {
blocksSuccesses++;
userOperations.add(1);
}
break;
case 3: // Monitoring: Check execution history
if (
check(response, {
"Execution Monitor: Recent executions loaded successfully": (r) =>
r.status === 200,
})
) {
executionsSuccesses++;
userOperations.add(1);
}
break;
}
}
console.log(
`✅ VU ${__VU} completed realistic workflows: ${creditsSuccesses} dashboard checks, ${graphsSuccesses} graph views, ${blocksSuccesses} block explorations, ${executionsSuccesses} execution monitors`,
);
// Think time between user sessions
sleep(Math.random() * 3 + 1); // 1-4 seconds
}
function userProfileJourney(headers) {
const startTime = Date.now();
// 1. Get user credits (JWT-only endpoint)
const creditsResponse = http.get(`${config.API_BASE_URL}/api/credits`, {
headers,
});
userOperations.add(1);
check(creditsResponse, {
"User credits loaded successfully": (r) => r.status === 200,
});
// 2. Check onboarding status
const onboardingResponse = http.get(`${config.API_BASE_URL}/api/onboarding`, {
headers,
});
userOperations.add(1);
check(onboardingResponse, {
"Onboarding status loaded": (r) => r.status === 200,
});
apiResponseTime.add(Date.now() - startTime);
}
function graphManagementJourney(headers) {
const startTime = Date.now();
// 1. List existing graphs
const listResponse = http.get(`${config.API_BASE_URL}/api/graphs`, {
headers,
});
graphOperations.add(1);
const listSuccess = check(listResponse, {
"Graphs list loaded successfully": (r) => r.status === 200,
});
// 2. Create a new graph (20% of users)
if (Math.random() < 0.2) {
const graphData = generateTestGraph();
const createResponse = http.post(
`${config.API_BASE_URL}/api/graphs`,
JSON.stringify(graphData),
{ headers },
);
graphOperations.add(1);
const createSuccess = check(createResponse, {
"Graph created successfully": (r) => r.status === 200,
});
if (createSuccess && createResponse.status === 200) {
try {
const createdGraph = JSON.parse(createResponse.body);
// 3. Get the created graph details
const getResponse = http.get(
`${config.API_BASE_URL}/api/graphs/${createdGraph.id}`,
{ headers },
);
graphOperations.add(1);
check(getResponse, {
"Graph details loaded": (r) => r.status === 200,
});
// 4. Execute the graph (50% chance)
if (Math.random() < 0.5) {
executeGraphScenario(createdGraph, headers);
}
// 5. Create schedule for graph (10% chance)
if (Math.random() < 0.1) {
createScheduleScenario(createdGraph.id, headers);
}
} catch (error) {
console.error("Error handling created graph:", error);
}
}
}
// 3. Work with existing graphs (if any)
if (listSuccess && listResponse.status === 200) {
try {
const existingGraphs = JSON.parse(listResponse.body);
if (existingGraphs.length > 0) {
// Pick a random existing graph
const randomGraph =
existingGraphs[Math.floor(Math.random() * existingGraphs.length)];
// Get graph details
const getResponse = http.get(
`${config.API_BASE_URL}/api/graphs/${randomGraph.id}`,
{ headers },
);
graphOperations.add(1);
check(getResponse, {
"Existing graph details loaded": (r) => r.status === 200,
});
// Execute existing graph (30% chance)
if (Math.random() < 0.3) {
executeGraphScenario(randomGraph, headers);
}
}
} catch (error) {
console.error("Error working with existing graphs:", error);
}
}
apiResponseTime.add(Date.now() - startTime);
}
function executeGraphScenario(graph, headers) {
const startTime = Date.now();
const executionInputs = generateExecutionInputs();
const executeResponse = http.post(
`${config.API_BASE_URL}/api/graphs/${graph.id}/execute/${graph.version}`,
JSON.stringify({
inputs: executionInputs,
credentials_inputs: {},
}),
{ headers },
);
executionOperations.add(1);
const executeSuccess = check(executeResponse, {
"Graph execution initiated": (r) => r.status === 200 || r.status === 402, // 402 = insufficient credits
});
if (executeSuccess && executeResponse.status === 200) {
try {
const execution = JSON.parse(executeResponse.body);
// Monitor execution status (simulate user checking results)
// Note: setTimeout doesn't work in k6, so we'll check status immediately
const statusResponse = http.get(
`${config.API_BASE_URL}/api/graphs/${graph.id}/executions/${execution.id}`,
{ headers },
);
executionOperations.add(1);
check(statusResponse, {
"Execution status retrieved": (r) => r.status === 200,
});
} catch (error) {
console.error("Error monitoring execution:", error);
}
}
apiResponseTime.add(Date.now() - startTime);
}
function createScheduleScenario(graphId, headers) {
const scheduleData = generateScheduleData(graphId);
const scheduleResponse = http.post(
`${config.API_BASE_URL}/api/graphs/${graphId}/schedules`,
JSON.stringify(scheduleData),
{ headers },
);
graphOperations.add(1);
check(scheduleResponse, {
"Schedule created successfully": (r) => r.status === 200,
});
}
function blockOperationsJourney(headers) {
const startTime = Date.now();
// 1. Get available blocks
const blocksResponse = http.get(`${config.API_BASE_URL}/api/blocks`, {
headers,
});
userOperations.add(1);
const blocksSuccess = check(blocksResponse, {
"Blocks list loaded": (r) => r.status === 200,
});
// 2. Execute some blocks directly (simulate testing)
if (blocksSuccess && Math.random() < 0.3) {
// Execute GetCurrentTimeBlock (simple, fast block)
const timeBlockResponse = http.post(
`${config.API_BASE_URL}/api/blocks/a892b8d9-3e4e-4e9c-9c1e-75f8efcf1bfa/execute`,
JSON.stringify({
trigger: "test",
format_type: {
discriminator: "iso8601",
timezone: "UTC",
},
}),
{ headers },
);
userOperations.add(1);
check(timeBlockResponse, {
"Time block executed or handled gracefully": (r) =>
r.status === 200 || r.status === 500, // 500 = user_context missing (expected)
});
}
apiResponseTime.add(Date.now() - startTime);
}
function systemOperationsJourney(headers) {
const startTime = Date.now();
// 1. Check executions list (simulate monitoring)
const executionsResponse = http.get(`${config.API_BASE_URL}/api/executions`, {
headers,
});
userOperations.add(1);
check(executionsResponse, {
"Executions list loaded": (r) => r.status === 200,
});
// 2. Check schedules (if any)
const schedulesResponse = http.get(`${config.API_BASE_URL}/api/schedules`, {
headers,
});
userOperations.add(1);
check(schedulesResponse, {
"Schedules list loaded": (r) => r.status === 200,
});
// 3. Check API keys (simulate user managing access)
if (Math.random() < 0.1) {
// 10% of users check API keys
const apiKeysResponse = http.get(`${config.API_BASE_URL}/api/api-keys`, {
headers,
});
userOperations.add(1);
check(apiKeysResponse, {
"API keys list loaded": (r) => r.status === 200,
});
// Occasionally create new API key (5% chance)
if (Math.random() < 0.05) {
const keyData = generateAPIKeyRequest();
const createKeyResponse = http.post(
`${config.API_BASE_URL}/api/api-keys`,
JSON.stringify(keyData),
{ headers },
);
userOperations.add(1);
check(createKeyResponse, {
"API key created successfully": (r) => r.status === 200,
});
}
}
apiResponseTime.add(Date.now() - startTime);
}
export function teardown(data) {
console.log("🧹 Cleaning up load test...");
console.log(`Total user operations: ${userOperations.value}`);
console.log(`Total graph operations: ${graphOperations.value}`);
console.log(`Total execution operations: ${executionOperations.value}`);
const testDuration = Date.now() - data.timestamp;
console.log(`Test completed in ${testDuration}ms`);
}

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@@ -1,536 +0,0 @@
import { check } from "k6";
import http from "k6/http";
import { Counter } from "k6/metrics";
import { getEnvironmentConfig } from "../../configs/environment.js";
import { getPreAuthenticatedHeaders } from "../../configs/pre-authenticated-tokens.js";
const config = getEnvironmentConfig();
const BASE_URL = config.API_BASE_URL;
// Custom metrics
const libraryRequests = new Counter("library_requests_total");
const successfulRequests = new Counter("successful_requests_total");
const failedRequests = new Counter("failed_requests_total");
const authenticationAttempts = new Counter("authentication_attempts_total");
const authenticationSuccesses = new Counter("authentication_successes_total");
// Test configuration
const VUS = parseInt(__ENV.VUS) || 5;
const DURATION = __ENV.DURATION || "2m";
const RAMP_UP = __ENV.RAMP_UP || "30s";
const RAMP_DOWN = __ENV.RAMP_DOWN || "30s";
const REQUESTS_PER_VU = parseInt(__ENV.REQUESTS_PER_VU) || 5;
// Performance thresholds for authenticated endpoints
const THRESHOLD_P95 = parseInt(__ENV.THRESHOLD_P95) || 10000; // 10s for authenticated endpoints
const THRESHOLD_P99 = parseInt(__ENV.THRESHOLD_P99) || 20000; // 20s for authenticated endpoints
const THRESHOLD_ERROR_RATE = parseFloat(__ENV.THRESHOLD_ERROR_RATE) || 0.1; // 10% error rate
const THRESHOLD_CHECK_RATE = parseFloat(__ENV.THRESHOLD_CHECK_RATE) || 0.85; // 85% success rate
export const options = {
stages: [
{ duration: RAMP_UP, target: VUS },
{ duration: DURATION, target: VUS },
{ duration: RAMP_DOWN, target: 0 },
],
thresholds: {
http_req_duration: [
{ threshold: `p(95)<${THRESHOLD_P95}`, abortOnFail: false },
{ threshold: `p(99)<${THRESHOLD_P99}`, abortOnFail: false },
],
http_req_failed: [
{ threshold: `rate<${THRESHOLD_ERROR_RATE}`, abortOnFail: false },
],
checks: [{ threshold: `rate>${THRESHOLD_CHECK_RATE}`, abortOnFail: false }],
},
tags: {
test_type: "marketplace_library_authorized",
environment: __ENV.K6_ENVIRONMENT || "DEV",
},
};
export default function () {
console.log(`📚 VU ${__VU} starting authenticated library journey...`);
// Get pre-authenticated headers
const headers = getPreAuthenticatedHeaders(__VU);
if (!headers || !headers.Authorization) {
console.log(`❌ VU ${__VU} authentication failed, skipping iteration`);
authenticationAttempts.add(1);
return;
}
authenticationAttempts.add(1);
authenticationSuccesses.add(1);
// Run multiple library operations per iteration
for (let i = 0; i < REQUESTS_PER_VU; i++) {
console.log(
`🔄 VU ${__VU} starting library operation ${i + 1}/${REQUESTS_PER_VU}...`,
);
authenticatedLibraryJourney(headers);
}
}
function authenticatedLibraryJourney(headers) {
const journeyStart = Date.now();
// Step 1: Get user's library agents
console.log(`📖 VU ${__VU} fetching user library agents...`);
const libraryAgentsResponse = http.get(
`${BASE_URL}/api/library/agents?page=1&page_size=20`,
{ headers },
);
libraryRequests.add(1);
const librarySuccess = check(libraryAgentsResponse, {
"Library agents endpoint returns 200": (r) => r.status === 200,
"Library agents response has data": (r) => {
try {
const json = r.json();
return json && json.agents && Array.isArray(json.agents);
} catch {
return false;
}
},
"Library agents response time < 10s": (r) => r.timings.duration < 10000,
});
if (librarySuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
console.log(
`⚠️ VU ${__VU} library agents request failed: ${libraryAgentsResponse.status} - ${libraryAgentsResponse.body}`,
);
}
// Step 2: Get favorite agents
console.log(`⭐ VU ${__VU} fetching favorite library agents...`);
const favoriteAgentsResponse = http.get(
`${BASE_URL}/api/library/agents/favorites?page=1&page_size=10`,
{ headers },
);
libraryRequests.add(1);
const favoritesSuccess = check(favoriteAgentsResponse, {
"Favorite agents endpoint returns 200": (r) => r.status === 200,
"Favorite agents response has data": (r) => {
try {
const json = r.json();
return json && json.agents !== undefined && Array.isArray(json.agents);
} catch {
return false;
}
},
"Favorite agents response time < 10s": (r) => r.timings.duration < 10000,
});
if (favoritesSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
console.log(
`⚠️ VU ${__VU} favorite agents request failed: ${favoriteAgentsResponse.status}`,
);
}
// Step 3: Add marketplace agent to library (simulate discovering and adding an agent)
console.log(`🛍️ VU ${__VU} browsing marketplace to add agent...`);
// First get available store agents to find one to add
const storeAgentsResponse = http.get(
`${BASE_URL}/api/store/agents?page=1&page_size=5`,
);
libraryRequests.add(1);
const storeAgentsSuccess = check(storeAgentsResponse, {
"Store agents endpoint returns 200": (r) => r.status === 200,
"Store agents response has data": (r) => {
try {
const json = r.json();
return (
json &&
json.agents &&
Array.isArray(json.agents) &&
json.agents.length > 0
);
} catch {
return false;
}
},
});
if (storeAgentsSuccess) {
successfulRequests.add(1);
try {
const storeAgentsJson = storeAgentsResponse.json();
if (storeAgentsJson?.agents && storeAgentsJson.agents.length > 0) {
const randomStoreAgent =
storeAgentsJson.agents[
Math.floor(Math.random() * storeAgentsJson.agents.length)
];
if (randomStoreAgent?.store_listing_version_id) {
console.log(
` VU ${__VU} adding agent "${randomStoreAgent.name || "Unknown"}" to library...`,
);
const addAgentPayload = {
store_listing_version_id: randomStoreAgent.store_listing_version_id,
};
const addAgentResponse = http.post(
`${BASE_URL}/api/library/agents`,
JSON.stringify(addAgentPayload),
{ headers },
);
libraryRequests.add(1);
const addAgentSuccess = check(addAgentResponse, {
"Add agent returns 201 or 200 (created/already exists)": (r) =>
r.status === 201 || r.status === 200,
"Add agent response has id": (r) => {
try {
const json = r.json();
return json && json.id;
} catch {
return false;
}
},
"Add agent response time < 15s": (r) => r.timings.duration < 15000,
});
if (addAgentSuccess) {
successfulRequests.add(1);
// Step 4: Update the added agent (mark as favorite)
try {
const addedAgentJson = addAgentResponse.json();
if (addedAgentJson?.id) {
console.log(`⭐ VU ${__VU} marking agent as favorite...`);
const updatePayload = {
is_favorite: true,
auto_update_version: true,
};
const updateAgentResponse = http.patch(
`${BASE_URL}/api/library/agents/${addedAgentJson.id}`,
JSON.stringify(updatePayload),
{ headers },
);
libraryRequests.add(1);
const updateSuccess = check(updateAgentResponse, {
"Update agent returns 200": (r) => r.status === 200,
"Update agent response has updated data": (r) => {
try {
const json = r.json();
return json && json.id && json.is_favorite === true;
} catch {
return false;
}
},
"Update agent response time < 10s": (r) =>
r.timings.duration < 10000,
});
if (updateSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
console.log(
`⚠️ VU ${__VU} update agent failed: ${updateAgentResponse.status}`,
);
}
// Step 5: Get specific library agent details
console.log(`📄 VU ${__VU} fetching agent details...`);
const agentDetailsResponse = http.get(
`${BASE_URL}/api/library/agents/${addedAgentJson.id}`,
{ headers },
);
libraryRequests.add(1);
const detailsSuccess = check(agentDetailsResponse, {
"Agent details returns 200": (r) => r.status === 200,
"Agent details response has complete data": (r) => {
try {
const json = r.json();
return json && json.id && json.name && json.graph_id;
} catch {
return false;
}
},
"Agent details response time < 10s": (r) =>
r.timings.duration < 10000,
});
if (detailsSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
console.log(
`⚠️ VU ${__VU} agent details failed: ${agentDetailsResponse.status}`,
);
}
// Step 6: Fork the library agent (simulate user customization)
console.log(`🍴 VU ${__VU} forking agent for customization...`);
const forkAgentResponse = http.post(
`${BASE_URL}/api/library/agents/${addedAgentJson.id}/fork`,
"",
{ headers },
);
libraryRequests.add(1);
const forkSuccess = check(forkAgentResponse, {
"Fork agent returns 200": (r) => r.status === 200,
"Fork agent response has new agent data": (r) => {
try {
const json = r.json();
return json && json.id && json.id !== addedAgentJson.id; // Should be different ID
} catch {
return false;
}
},
"Fork agent response time < 15s": (r) =>
r.timings.duration < 15000,
});
if (forkSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
console.log(
`⚠️ VU ${__VU} fork agent failed: ${forkAgentResponse.status}`,
);
}
}
} catch (e) {
console.warn(
`⚠️ VU ${__VU} failed to parse added agent response: ${e}`,
);
failedRequests.add(1);
}
} else {
failedRequests.add(1);
console.log(
`⚠️ VU ${__VU} add agent failed: ${addAgentResponse.status} - ${addAgentResponse.body}`,
);
}
}
}
} catch (e) {
console.warn(`⚠️ VU ${__VU} failed to parse store agents data: ${e}`);
failedRequests.add(1);
}
} else {
failedRequests.add(1);
console.log(
`⚠️ VU ${__VU} store agents request failed: ${storeAgentsResponse.status}`,
);
}
// Step 7: Search library agents
const searchTerms = ["automation", "api", "data", "social", "productivity"];
const randomSearchTerm =
searchTerms[Math.floor(Math.random() * searchTerms.length)];
console.log(`🔍 VU ${__VU} searching library for "${randomSearchTerm}"...`);
const searchLibraryResponse = http.get(
`${BASE_URL}/api/library/agents?search_term=${encodeURIComponent(randomSearchTerm)}&page=1&page_size=10`,
{ headers },
);
libraryRequests.add(1);
const searchLibrarySuccess = check(searchLibraryResponse, {
"Search library returns 200": (r) => r.status === 200,
"Search library response has data": (r) => {
try {
const json = r.json();
return json && json.agents !== undefined && Array.isArray(json.agents);
} catch {
return false;
}
},
"Search library response time < 10s": (r) => r.timings.duration < 10000,
});
if (searchLibrarySuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
console.log(
`⚠️ VU ${__VU} search library failed: ${searchLibraryResponse.status}`,
);
}
// Step 8: Get library agent by graph ID (simulate finding agent by backend graph)
if (libraryAgentsResponse.status === 200) {
try {
const libraryJson = libraryAgentsResponse.json();
if (libraryJson?.agents && libraryJson.agents.length > 0) {
const randomLibraryAgent =
libraryJson.agents[
Math.floor(Math.random() * libraryJson.agents.length)
];
if (randomLibraryAgent?.graph_id) {
console.log(
`🔗 VU ${__VU} fetching agent by graph ID "${randomLibraryAgent.graph_id}"...`,
);
const agentByGraphResponse = http.get(
`${BASE_URL}/api/library/agents/by-graph/${randomLibraryAgent.graph_id}`,
{ headers },
);
libraryRequests.add(1);
const agentByGraphSuccess = check(agentByGraphResponse, {
"Agent by graph ID returns 200": (r) => r.status === 200,
"Agent by graph response has data": (r) => {
try {
const json = r.json();
return (
json &&
json.id &&
json.graph_id === randomLibraryAgent.graph_id
);
} catch {
return false;
}
},
"Agent by graph response time < 10s": (r) =>
r.timings.duration < 10000,
});
if (agentByGraphSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
console.log(
`⚠️ VU ${__VU} agent by graph request failed: ${agentByGraphResponse.status}`,
);
}
}
}
} catch (e) {
console.warn(
`⚠️ VU ${__VU} failed to parse library agents for graph lookup: ${e}`,
);
failedRequests.add(1);
}
}
const journeyDuration = Date.now() - journeyStart;
console.log(
`✅ VU ${__VU} completed authenticated library journey in ${journeyDuration}ms`,
);
}
export function handleSummary(data) {
const summary = {
test_type: "Marketplace Library Authorized Access Load Test",
environment: __ENV.K6_ENVIRONMENT || "DEV",
configuration: {
virtual_users: VUS,
duration: DURATION,
ramp_up: RAMP_UP,
ramp_down: RAMP_DOWN,
requests_per_vu: REQUESTS_PER_VU,
},
performance_metrics: {
total_requests: data.metrics.http_reqs?.count || 0,
failed_requests: data.metrics.http_req_failed?.values?.passes || 0,
avg_response_time: data.metrics.http_req_duration?.values?.avg || 0,
p95_response_time: data.metrics.http_req_duration?.values?.p95 || 0,
p99_response_time: data.metrics.http_req_duration?.values?.p99 || 0,
},
custom_metrics: {
library_requests: data.metrics.library_requests_total?.values?.count || 0,
successful_requests:
data.metrics.successful_requests_total?.values?.count || 0,
failed_requests: data.metrics.failed_requests_total?.values?.count || 0,
authentication_attempts:
data.metrics.authentication_attempts_total?.values?.count || 0,
authentication_successes:
data.metrics.authentication_successes_total?.values?.count || 0,
},
thresholds_met: {
p95_threshold:
(data.metrics.http_req_duration?.values?.p95 || 0) < THRESHOLD_P95,
p99_threshold:
(data.metrics.http_req_duration?.values?.p99 || 0) < THRESHOLD_P99,
error_rate_threshold:
(data.metrics.http_req_failed?.values?.rate || 0) <
THRESHOLD_ERROR_RATE,
check_rate_threshold:
(data.metrics.checks?.values?.rate || 0) > THRESHOLD_CHECK_RATE,
},
authentication_metrics: {
auth_success_rate:
(data.metrics.authentication_successes_total?.values?.count || 0) /
Math.max(
1,
data.metrics.authentication_attempts_total?.values?.count || 0,
),
},
user_journey_coverage: [
"Authenticate with valid credentials",
"Fetch user library agents",
"Browse favorite library agents",
"Discover marketplace agents",
"Add marketplace agent to library",
"Update agent preferences (favorites)",
"View detailed agent information",
"Fork agent for customization",
"Search library agents by term",
"Lookup agent by graph ID",
],
};
console.log("\n📚 MARKETPLACE LIBRARY AUTHORIZED TEST SUMMARY");
console.log("==============================================");
console.log(`Environment: ${summary.environment}`);
console.log(`Virtual Users: ${summary.configuration.virtual_users}`);
console.log(`Duration: ${summary.configuration.duration}`);
console.log(`Requests per VU: ${summary.configuration.requests_per_vu}`);
console.log(`Total Requests: ${summary.performance_metrics.total_requests}`);
console.log(
`Successful Requests: ${summary.custom_metrics.successful_requests}`,
);
console.log(`Failed Requests: ${summary.custom_metrics.failed_requests}`);
console.log(
`Auth Success Rate: ${Math.round(summary.authentication_metrics.auth_success_rate * 100)}%`,
);
console.log(
`Average Response Time: ${Math.round(summary.performance_metrics.avg_response_time)}ms`,
);
console.log(
`95th Percentile: ${Math.round(summary.performance_metrics.p95_response_time)}ms`,
);
console.log(
`99th Percentile: ${Math.round(summary.performance_metrics.p99_response_time)}ms`,
);
console.log("\n🎯 Threshold Status:");
console.log(
`P95 < ${THRESHOLD_P95}ms: ${summary.thresholds_met.p95_threshold ? "✅" : "❌"}`,
);
console.log(
`P99 < ${THRESHOLD_P99}ms: ${summary.thresholds_met.p99_threshold ? "✅" : "❌"}`,
);
console.log(
`Error Rate < ${THRESHOLD_ERROR_RATE * 100}%: ${summary.thresholds_met.error_rate_threshold ? "✅" : "❌"}`,
);
console.log(
`Check Rate > ${THRESHOLD_CHECK_RATE * 100}%: ${summary.thresholds_met.check_rate_threshold ? "✅" : "❌"}`,
);
return {
stdout: JSON.stringify(summary, null, 2),
};
}

View File

@@ -1,465 +0,0 @@
import { check } from "k6";
import http from "k6/http";
import { Counter } from "k6/metrics";
import { getEnvironmentConfig } from "../../configs/environment.js";
const config = getEnvironmentConfig();
const BASE_URL = config.API_BASE_URL;
// Custom metrics
const marketplaceRequests = new Counter("marketplace_requests_total");
const successfulRequests = new Counter("successful_requests_total");
const failedRequests = new Counter("failed_requests_total");
// HTTP error tracking
const httpErrors = new Counter("http_errors_by_status");
// Enhanced error logging function
function logHttpError(response, endpoint, method = "GET") {
if (response.status !== 200) {
console.error(
`❌ VU ${__VU} ${method} ${endpoint} failed: status=${response.status}, error=${response.error || "unknown"}, body=${response.body ? response.body.substring(0, 200) : "empty"}`,
);
httpErrors.add(1, {
status: response.status,
endpoint: endpoint,
method: method,
});
}
}
// Test configuration
const VUS = parseInt(__ENV.VUS) || 10;
const DURATION = __ENV.DURATION || "2m";
const RAMP_UP = __ENV.RAMP_UP || "30s";
const RAMP_DOWN = __ENV.RAMP_DOWN || "30s";
// Performance thresholds for marketplace browsing
const REQUEST_TIMEOUT = 60000; // 60s per request timeout
const THRESHOLD_P95 = parseInt(__ENV.THRESHOLD_P95) || 5000; // 5s for public endpoints
const THRESHOLD_P99 = parseInt(__ENV.THRESHOLD_P99) || 10000; // 10s for public endpoints
const THRESHOLD_ERROR_RATE = parseFloat(__ENV.THRESHOLD_ERROR_RATE) || 0.05; // 5% error rate
const THRESHOLD_CHECK_RATE = parseFloat(__ENV.THRESHOLD_CHECK_RATE) || 0.95; // 95% success rate
export const options = {
stages: [
{ duration: RAMP_UP, target: VUS },
{ duration: DURATION, target: VUS },
{ duration: RAMP_DOWN, target: 0 },
],
// Thresholds disabled to collect all results regardless of performance
// thresholds: {
// http_req_duration: [
// { threshold: `p(95)<${THRESHOLD_P95}`, abortOnFail: false },
// { threshold: `p(99)<${THRESHOLD_P99}`, abortOnFail: false },
// ],
// http_req_failed: [{ threshold: `rate<${THRESHOLD_ERROR_RATE}`, abortOnFail: false }],
// checks: [{ threshold: `rate>${THRESHOLD_CHECK_RATE}`, abortOnFail: false }],
// },
tags: {
test_type: "marketplace_public_access",
environment: __ENV.K6_ENVIRONMENT || "DEV",
},
};
export default function () {
console.log(`🛒 VU ${__VU} starting marketplace browsing journey...`);
// Simulate realistic user marketplace browsing journey
marketplaceBrowsingJourney();
}
function marketplaceBrowsingJourney() {
const journeyStart = Date.now();
// Step 1: Browse marketplace homepage - get featured agents
console.log(`🏪 VU ${__VU} browsing marketplace homepage...`);
const featuredAgentsResponse = http.get(
`${BASE_URL}/api/store/agents?featured=true&page=1&page_size=10`,
);
logHttpError(
featuredAgentsResponse,
"/api/store/agents?featured=true",
"GET",
);
marketplaceRequests.add(1);
const featuredSuccess = check(featuredAgentsResponse, {
"Featured agents endpoint returns 200": (r) => r.status === 200,
"Featured agents response has data": (r) => {
try {
const json = r.json();
return json && json.agents && Array.isArray(json.agents);
} catch {
return false;
}
},
"Featured agents responds within 60s": (r) =>
r.timings.duration < REQUEST_TIMEOUT,
});
if (featuredSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
}
// Step 2: Browse all agents with pagination
console.log(`📋 VU ${__VU} browsing all agents...`);
const allAgentsResponse = http.get(
`${BASE_URL}/api/store/agents?page=1&page_size=20`,
);
logHttpError(allAgentsResponse, "/api/store/agents", "GET");
marketplaceRequests.add(1);
const allAgentsSuccess = check(allAgentsResponse, {
"All agents endpoint returns 200": (r) => r.status === 200,
"All agents response has data": (r) => {
try {
const json = r.json();
return (
json &&
json.agents &&
Array.isArray(json.agents) &&
json.agents.length > 0
);
} catch {
return false;
}
},
"All agents responds within 60s": (r) =>
r.timings.duration < REQUEST_TIMEOUT,
});
if (allAgentsSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
}
// Step 3: Search for specific agents
const searchQueries = [
"automation",
"social media",
"data analysis",
"productivity",
];
const randomQuery =
searchQueries[Math.floor(Math.random() * searchQueries.length)];
console.log(`🔍 VU ${__VU} searching for "${randomQuery}" agents...`);
const searchResponse = http.get(
`${BASE_URL}/api/store/agents?search_query=${encodeURIComponent(randomQuery)}&page=1&page_size=10`,
);
logHttpError(searchResponse, "/api/store/agents (search)", "GET");
marketplaceRequests.add(1);
const searchSuccess = check(searchResponse, {
"Search agents endpoint returns 200": (r) => r.status === 200,
"Search agents response has data": (r) => {
try {
const json = r.json();
return json && json.agents && Array.isArray(json.agents);
} catch {
return false;
}
},
"Search agents responds within 60s": (r) =>
r.timings.duration < REQUEST_TIMEOUT,
});
if (searchSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
}
// Step 4: Browse agents by category
const categories = ["AI", "PRODUCTIVITY", "COMMUNICATION", "DATA", "SOCIAL"];
const randomCategory =
categories[Math.floor(Math.random() * categories.length)];
console.log(`📂 VU ${__VU} browsing "${randomCategory}" category...`);
const categoryResponse = http.get(
`${BASE_URL}/api/store/agents?category=${randomCategory}&page=1&page_size=15`,
);
logHttpError(categoryResponse, "/api/store/agents (category)", "GET");
marketplaceRequests.add(1);
const categorySuccess = check(categoryResponse, {
"Category agents endpoint returns 200": (r) => r.status === 200,
"Category agents response has data": (r) => {
try {
const json = r.json();
return json && json.agents && Array.isArray(json.agents);
} catch {
return false;
}
},
"Category agents responds within 60s": (r) =>
r.timings.duration < REQUEST_TIMEOUT,
});
if (categorySuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
}
// Step 5: Get specific agent details (simulate clicking on an agent)
if (allAgentsResponse.status === 200) {
try {
const allAgentsJson = allAgentsResponse.json();
if (allAgentsJson?.agents && allAgentsJson.agents.length > 0) {
const randomAgent =
allAgentsJson.agents[
Math.floor(Math.random() * allAgentsJson.agents.length)
];
if (randomAgent?.creator_username && randomAgent?.slug) {
console.log(
`📄 VU ${__VU} viewing agent details for "${randomAgent.slug}"...`,
);
const agentDetailsResponse = http.get(
`${BASE_URL}/api/store/agents/${encodeURIComponent(randomAgent.creator_username)}/${encodeURIComponent(randomAgent.slug)}`,
);
logHttpError(
agentDetailsResponse,
"/api/store/agents/{creator}/{slug}",
"GET",
);
marketplaceRequests.add(1);
const agentDetailsSuccess = check(agentDetailsResponse, {
"Agent details endpoint returns 200": (r) => r.status === 200,
"Agent details response has data": (r) => {
try {
const json = r.json();
return json && json.id && json.name && json.description;
} catch {
return false;
}
},
"Agent details responds within 60s": (r) =>
r.timings.duration < REQUEST_TIMEOUT,
});
if (agentDetailsSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
}
}
}
} catch (e) {
console.warn(
`⚠️ VU ${__VU} failed to parse agents data for details lookup: ${e}`,
);
failedRequests.add(1);
}
}
// Step 6: Browse creators
console.log(`👥 VU ${__VU} browsing creators...`);
const creatorsResponse = http.get(
`${BASE_URL}/api/store/creators?page=1&page_size=20`,
);
logHttpError(creatorsResponse, "/api/store/creators", "GET");
marketplaceRequests.add(1);
const creatorsSuccess = check(creatorsResponse, {
"Creators endpoint returns 200": (r) => r.status === 200,
"Creators response has data": (r) => {
try {
const json = r.json();
return json && json.creators && Array.isArray(json.creators);
} catch {
return false;
}
},
"Creators responds within 60s": (r) => r.timings.duration < REQUEST_TIMEOUT,
});
if (creatorsSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
}
// Step 7: Get featured creators
console.log(`⭐ VU ${__VU} browsing featured creators...`);
const featuredCreatorsResponse = http.get(
`${BASE_URL}/api/store/creators?featured=true&page=1&page_size=10`,
);
logHttpError(
featuredCreatorsResponse,
"/api/store/creators?featured=true",
"GET",
);
marketplaceRequests.add(1);
const featuredCreatorsSuccess = check(featuredCreatorsResponse, {
"Featured creators endpoint returns 200": (r) => r.status === 200,
"Featured creators response has data": (r) => {
try {
const json = r.json();
return json && json.creators && Array.isArray(json.creators);
} catch {
return false;
}
},
"Featured creators responds within 60s": (r) =>
r.timings.duration < REQUEST_TIMEOUT,
});
if (featuredCreatorsSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
}
// Step 8: Get specific creator details (simulate clicking on a creator)
if (creatorsResponse.status === 200) {
try {
const creatorsJson = creatorsResponse.json();
if (creatorsJson?.creators && creatorsJson.creators.length > 0) {
const randomCreator =
creatorsJson.creators[
Math.floor(Math.random() * creatorsJson.creators.length)
];
if (randomCreator?.username) {
console.log(
`👤 VU ${__VU} viewing creator details for "${randomCreator.username}"...`,
);
const creatorDetailsResponse = http.get(
`${BASE_URL}/api/store/creator/${encodeURIComponent(randomCreator.username)}`,
);
logHttpError(
creatorDetailsResponse,
"/api/store/creator/{username}",
"GET",
);
marketplaceRequests.add(1);
const creatorDetailsSuccess = check(creatorDetailsResponse, {
"Creator details endpoint returns 200": (r) => r.status === 200,
"Creator details response has data": (r) => {
try {
const json = r.json();
return json && json.username && json.description !== undefined;
} catch {
return false;
}
},
"Creator details responds within 60s": (r) =>
r.timings.duration < REQUEST_TIMEOUT,
});
if (creatorDetailsSuccess) {
successfulRequests.add(1);
} else {
failedRequests.add(1);
}
}
}
} catch (e) {
console.warn(
`⚠️ VU ${__VU} failed to parse creators data for details lookup: ${e}`,
);
failedRequests.add(1);
}
}
const journeyDuration = Date.now() - journeyStart;
console.log(
`✅ VU ${__VU} completed marketplace browsing journey in ${journeyDuration}ms`,
);
}
export function handleSummary(data) {
const summary = {
test_type: "Marketplace Public Access Load Test",
environment: __ENV.K6_ENVIRONMENT || "DEV",
configuration: {
virtual_users: VUS,
duration: DURATION,
ramp_up: RAMP_UP,
ramp_down: RAMP_DOWN,
},
performance_metrics: {
total_requests: data.metrics.http_reqs?.count || 0,
failed_requests: data.metrics.http_req_failed?.values?.passes || 0,
avg_response_time: data.metrics.http_req_duration?.values?.avg || 0,
p95_response_time: data.metrics.http_req_duration?.values?.p95 || 0,
p99_response_time: data.metrics.http_req_duration?.values?.p99 || 0,
},
custom_metrics: {
marketplace_requests:
data.metrics.marketplace_requests_total?.values?.count || 0,
successful_requests:
data.metrics.successful_requests_total?.values?.count || 0,
failed_requests: data.metrics.failed_requests_total?.values?.count || 0,
},
thresholds_met: {
p95_threshold:
(data.metrics.http_req_duration?.values?.p95 || 0) < THRESHOLD_P95,
p99_threshold:
(data.metrics.http_req_duration?.values?.p99 || 0) < THRESHOLD_P99,
error_rate_threshold:
(data.metrics.http_req_failed?.values?.rate || 0) <
THRESHOLD_ERROR_RATE,
check_rate_threshold:
(data.metrics.checks?.values?.rate || 0) > THRESHOLD_CHECK_RATE,
},
user_journey_coverage: [
"Browse featured agents",
"Browse all agents with pagination",
"Search agents by keywords",
"Filter agents by category",
"View specific agent details",
"Browse creators directory",
"View featured creators",
"View specific creator details",
],
};
console.log("\n📊 MARKETPLACE PUBLIC ACCESS TEST SUMMARY");
console.log("==========================================");
console.log(`Environment: ${summary.environment}`);
console.log(`Virtual Users: ${summary.configuration.virtual_users}`);
console.log(`Duration: ${summary.configuration.duration}`);
console.log(`Total Requests: ${summary.performance_metrics.total_requests}`);
console.log(
`Successful Requests: ${summary.custom_metrics.successful_requests}`,
);
console.log(`Failed Requests: ${summary.custom_metrics.failed_requests}`);
console.log(
`Average Response Time: ${Math.round(summary.performance_metrics.avg_response_time)}ms`,
);
console.log(
`95th Percentile: ${Math.round(summary.performance_metrics.p95_response_time)}ms`,
);
console.log(
`99th Percentile: ${Math.round(summary.performance_metrics.p99_response_time)}ms`,
);
console.log("\n🎯 Threshold Status:");
console.log(
`P95 < ${THRESHOLD_P95}ms: ${summary.thresholds_met.p95_threshold ? "✅" : "❌"}`,
);
console.log(
`P99 < ${THRESHOLD_P99}ms: ${summary.thresholds_met.p99_threshold ? "✅" : "❌"}`,
);
console.log(
`Error Rate < ${THRESHOLD_ERROR_RATE * 100}%: ${summary.thresholds_met.error_rate_threshold ? "✅" : "❌"}`,
);
console.log(
`Check Rate > ${THRESHOLD_CHECK_RATE * 100}%: ${summary.thresholds_met.check_rate_threshold ? "✅" : "❌"}`,
);
return {
stdout: JSON.stringify(summary, null, 2),
};
}

View File

@@ -1,66 +0,0 @@
-- Fixes the refresh function+job introduced in 20250604130249_optimise_store_agent_and_creator_views
-- by improving the function to accept a schema parameter and updating the cron job to use it.
-- This resolves the issue where pg_cron jobs fail because they run in 'public' schema
-- but the materialized views exist in 'platform' schema.
-- Create parameterized refresh function that accepts schema name
CREATE OR REPLACE FUNCTION refresh_store_materialized_views()
RETURNS void
LANGUAGE plpgsql
AS $$
DECLARE
target_schema text := current_schema(); -- Use the current schema where the function is called
BEGIN
-- Use CONCURRENTLY for better performance during refresh
REFRESH MATERIALIZED VIEW CONCURRENTLY "mv_agent_run_counts";
REFRESH MATERIALIZED VIEW CONCURRENTLY "mv_review_stats";
RAISE NOTICE 'Materialized views refreshed in schema % at %', target_schema, NOW();
EXCEPTION
WHEN OTHERS THEN
-- Fallback to non-concurrent refresh if concurrent fails
REFRESH MATERIALIZED VIEW "mv_agent_run_counts";
REFRESH MATERIALIZED VIEW "mv_review_stats";
RAISE NOTICE 'Materialized views refreshed (non-concurrent) in schema % at %. Concurrent refresh failed due to: %', target_schema, NOW(), SQLERRM;
END;
$$;
-- Initial refresh + test of the function to ensure it works
SELECT refresh_store_materialized_views();
-- Re-create the cron job to use the improved function
DO $$
DECLARE
has_pg_cron BOOLEAN;
current_schema_name text := current_schema();
old_job_name text;
job_name text;
BEGIN
-- Check if pg_cron extension exists
SELECT EXISTS (SELECT 1 FROM pg_extension WHERE extname = 'pg_cron') INTO has_pg_cron;
IF has_pg_cron THEN
old_job_name := format('refresh-store-views-%s', current_schema_name);
job_name := format('refresh-store-views_%s', current_schema_name);
-- Try to unschedule existing job (ignore errors if it doesn't exist)
BEGIN
PERFORM cron.unschedule(old_job_name);
EXCEPTION WHEN OTHERS THEN
NULL;
END;
-- Schedule the new job with explicit schema parameter
PERFORM cron.schedule(
job_name,
'*/15 * * * *',
format('SET search_path TO %I; SELECT refresh_store_materialized_views();', current_schema_name)
);
RAISE NOTICE 'Scheduled job %; runs every 15 minutes for schema %', job_name, current_schema_name;
ELSE
RAISE WARNING '⚠️ Automatic refresh NOT configured - pg_cron is not available';
RAISE WARNING '⚠️ You must manually refresh views with: SELECT refresh_store_materialized_views();';
RAISE WARNING '⚠️ Or install pg_cron for automatic refresh in production';
END IF;
END;
$$;

View File

@@ -1,3 +0,0 @@
-- Re-create foreign key CreditTransaction <- User with ON DELETE NO ACTION
ALTER TABLE "CreditTransaction" DROP CONSTRAINT "CreditTransaction_userId_fkey";
ALTER TABLE "CreditTransaction" ADD CONSTRAINT "CreditTransaction_userId_fkey" FOREIGN KEY ("userId") REFERENCES "User"("id") ON DELETE NO ACTION ON UPDATE CASCADE;

View File

@@ -1,22 +0,0 @@
/*
Warnings:
- A unique constraint covering the columns `[shareToken]` on the table `AgentGraphExecution` will be added. If there are existing duplicate values, this will fail.
*/
-- AlterTable
ALTER TABLE "AgentGraphExecution" ADD COLUMN "isShared" BOOLEAN NOT NULL DEFAULT false,
ADD COLUMN "shareToken" TEXT,
ADD COLUMN "sharedAt" TIMESTAMP(3);
-- CreateIndex
CREATE UNIQUE INDEX "AgentGraphExecution_shareToken_key" ON "AgentGraphExecution"("shareToken");
-- CreateIndex
CREATE INDEX "AgentGraphExecution_shareToken_idx" ON "AgentGraphExecution"("shareToken");
-- RenameIndex
ALTER INDEX "APIKey_key_key" RENAME TO "APIKey_hash_key";
-- RenameIndex
ALTER INDEX "APIKey_prefix_name_idx" RENAME TO "APIKey_head_name_idx";

View File

@@ -1,53 +0,0 @@
-- Add instructions field to AgentGraph and StoreListingVersion tables and update StoreSubmission view
BEGIN;
-- AddColumn
ALTER TABLE "AgentGraph" ADD COLUMN "instructions" TEXT;
-- AddColumn
ALTER TABLE "StoreListingVersion" ADD COLUMN "instructions" TEXT;
-- Drop the existing view
DROP VIEW IF EXISTS "StoreSubmission";
-- Recreate the view with the new instructions field
CREATE VIEW "StoreSubmission" AS
SELECT
sl.id AS listing_id,
sl."owningUserId" AS user_id,
slv."agentGraphId" AS agent_id,
slv.version AS agent_version,
sl.slug,
COALESCE(slv.name, '') AS name,
slv."subHeading" AS sub_heading,
slv.description,
slv.instructions,
slv."imageUrls" AS image_urls,
slv."submittedAt" AS date_submitted,
slv."submissionStatus" AS status,
COALESCE(ar.run_count, 0::bigint) AS runs,
COALESCE(avg(sr.score::numeric), 0.0)::double precision AS rating,
slv.id AS store_listing_version_id,
slv."reviewerId" AS reviewer_id,
slv."reviewComments" AS review_comments,
slv."internalComments" AS internal_comments,
slv."reviewedAt" AS reviewed_at,
slv."changesSummary" AS changes_summary,
slv."videoUrl" AS video_url,
slv.categories
FROM "StoreListing" sl
JOIN "StoreListingVersion" slv ON slv."storeListingId" = sl.id
LEFT JOIN "StoreListingReview" sr ON sr."storeListingVersionId" = slv.id
LEFT JOIN (
SELECT "AgentGraphExecution"."agentGraphId", count(*) AS run_count
FROM "AgentGraphExecution"
GROUP BY "AgentGraphExecution"."agentGraphId"
) ar ON ar."agentGraphId" = slv."agentGraphId"
WHERE sl."isDeleted" = false
GROUP BY sl.id, sl."owningUserId", slv.id, slv."agentGraphId", slv.version, sl.slug, slv.name,
slv."subHeading", slv.description, slv.instructions, slv."imageUrls", slv."submittedAt",
slv."submissionStatus", slv."reviewerId", slv."reviewComments", slv."internalComments",
slv."reviewedAt", slv."changesSummary", slv."videoUrl", slv.categories, ar.run_count;
COMMIT;

View File

@@ -1,11 +0,0 @@
-- DropIndex
DROP INDEX "AgentGraph_userId_isActive_idx";
-- DropIndex
DROP INDEX "AgentGraphExecution_userId_idx";
-- CreateIndex
CREATE INDEX "AgentGraph_userId_isActive_id_version_idx" ON "AgentGraph"("userId", "isActive", "id", "version");
-- CreateIndex
CREATE INDEX "AgentGraphExecution_userId_isDeleted_createdAt_idx" ON "AgentGraphExecution"("userId", "isDeleted", "createdAt");

View File

@@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 2.1.4 and should not be changed by hand.
# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand.
[[package]]
name = "aio-pika"
@@ -338,7 +338,7 @@ description = "LTS Port of Python audioop"
optional = false
python-versions = ">=3.13"
groups = ["main"]
markers = "python_version == \"3.13\""
markers = "python_version >= \"3.13\""
files = [
{file = "audioop_lts-0.2.2-cp313-abi3-macosx_10_13_universal2.whl", hash = "sha256:fd3d4602dc64914d462924a08c1a9816435a2155d74f325853c1f1ac3b2d9800"},
{file = "audioop_lts-0.2.2-cp313-abi3-macosx_10_13_x86_64.whl", hash = "sha256:550c114a8df0aafe9a05442a1162dfc8fec37e9af1d625ae6060fed6e756f303"},
@@ -438,7 +438,7 @@ description = "Backport of asyncio.Runner, a context manager that controls event
optional = false
python-versions = "<3.11,>=3.8"
groups = ["main"]
markers = "python_version == \"3.10\""
markers = "python_version < \"3.11\""
files = [
{file = "backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5"},
{file = "backports_asyncio_runner-1.2.0.tar.gz", hash = "sha256:a5aa7b2b7d8f8bfcaa2b57313f70792df84e32a2a746f585213373f900b42162"},
@@ -451,7 +451,7 @@ description = "Backport of CPython tarfile module"
optional = false
python-versions = ">=3.8"
groups = ["main"]
markers = "python_version < \"3.12\""
markers = "python_version <= \"3.11\""
files = [
{file = "backports.tarfile-1.2.0-py3-none-any.whl", hash = "sha256:77e284d754527b01fb1e6fa8a1afe577858ebe4e9dad8919e34c862cb399bc34"},
{file = "backports_tarfile-1.2.0.tar.gz", hash = "sha256:d75e02c268746e1b8144c278978b6e98e85de6ad16f8e4b0844a154557eca991"},
@@ -1215,7 +1215,7 @@ files = [
{file = "exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10"},
{file = "exceptiongroup-1.3.0.tar.gz", hash = "sha256:b241f5885f560bc56a59ee63ca4c6a8bfa46ae4ad651af316d4e81817bb9fd88"},
]
markers = {dev = "python_version == \"3.10\""}
markers = {dev = "python_version < \"3.11\""}
[package.dependencies]
typing-extensions = {version = ">=4.6.0", markers = "python_version < \"3.13\""}
@@ -1581,16 +1581,16 @@ files = [
google-auth = ">=2.14.1,<3.0.0"
googleapis-common-protos = ">=1.56.2,<2.0.0"
grpcio = [
{version = ">=1.49.1,<2.0.0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
{version = ">=1.33.2,<2.0.0", optional = true, markers = "extra == \"grpc\""},
{version = ">=1.49.1,<2.0.0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
]
grpcio-status = [
{version = ">=1.49.1,<2.0.0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
{version = ">=1.33.2,<2.0.0", optional = true, markers = "extra == \"grpc\""},
{version = ">=1.49.1,<2.0.0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
]
proto-plus = [
{version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
{version = ">=1.22.3,<2.0.0"},
{version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
]
protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
requests = ">=2.18.0,<3.0.0"
@@ -1698,8 +1698,8 @@ files = [
google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.11.dev0,<3.0.0", extras = ["grpc"]}
google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0"
proto-plus = [
{version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
{version = ">=1.22.3,<2.0.0"},
{version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
]
protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
@@ -1759,9 +1759,9 @@ google-cloud-core = ">=2.0.0,<3.0.0"
grpc-google-iam-v1 = ">=0.12.4,<1.0.0"
opentelemetry-api = ">=1.9.0"
proto-plus = [
{version = ">=1.22.0,<2.0.0"},
{version = ">=1.22.2,<2.0.0", markers = "python_version >= \"3.11\""},
{version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
{version = ">=1.22.2,<2.0.0", markers = "python_version >= \"3.11\" and python_version < \"3.13\""},
{version = ">=1.22.0,<2.0.0", markers = "python_version < \"3.11\""},
]
protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
@@ -3253,7 +3253,7 @@ description = "Fundamental package for array computing in Python"
optional = false
python-versions = ">=3.10"
groups = ["main"]
markers = "python_version == \"3.10\""
markers = "python_version < \"3.11\""
files = [
{file = "numpy-2.2.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b412caa66f72040e6d268491a59f2c43bf03eb6c96dd8f0307829feb7fa2b6fb"},
{file = "numpy-2.2.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8e41fd67c52b86603a91c1a505ebaef50b3314de0213461c7a6e99c9a3beff90"},
@@ -3451,99 +3451,6 @@ files = [
importlib-metadata = ">=6.0,<8.8.0"
typing-extensions = ">=4.5.0"
[[package]]
name = "orjson"
version = "3.11.3"
description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
optional = false
python-versions = ">=3.9"
groups = ["main"]
files = [
{file = "orjson-3.11.3-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:29cb1f1b008d936803e2da3d7cba726fc47232c45df531b29edf0b232dd737e7"},
{file = "orjson-3.11.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:97dceed87ed9139884a55db8722428e27bd8452817fbf1869c58b49fecab1120"},
{file = "orjson-3.11.3-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:58533f9e8266cb0ac298e259ed7b4d42ed3fa0b78ce76860626164de49e0d467"},
{file = "orjson-3.11.3-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0c212cfdd90512fe722fa9bd620de4d46cda691415be86b2e02243242ae81873"},
{file = "orjson-3.11.3-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:5ff835b5d3e67d9207343effb03760c00335f8b5285bfceefd4dc967b0e48f6a"},
{file = "orjson-3.11.3-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f5aa4682912a450c2db89cbd92d356fef47e115dffba07992555542f344d301b"},
{file = "orjson-3.11.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d7d18dd34ea2e860553a579df02041845dee0af8985dff7f8661306f95504ddf"},
{file = "orjson-3.11.3-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d8b11701bc43be92ea42bd454910437b355dfb63696c06fe953ffb40b5f763b4"},
{file = "orjson-3.11.3-cp310-cp310-musllinux_1_2_armv7l.whl", hash = "sha256:90368277087d4af32d38bd55f9da2ff466d25325bf6167c8f382d8ee40cb2bbc"},
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]
[[package]]
name = "packaging"
version = "24.2"
@@ -3626,9 +3533,9 @@ files = [
[package.dependencies]
numpy = [
{version = ">=1.26.0", markers = "python_version >= \"3.12\""},
{version = ">=1.23.2", markers = "python_version == \"3.11\""},
{version = ">=1.22.4", markers = "python_version < \"3.11\""},
{version = ">=1.23.2", markers = "python_version == \"3.11\""},
{version = ">=1.26.0", markers = "python_version >= \"3.12\""},
]
python-dateutil = ">=2.8.2"
pytz = ">=2020.1"
@@ -3865,8 +3772,8 @@ pinecone-plugin-interface = ">=0.0.7,<0.0.8"
python-dateutil = ">=2.5.3"
typing-extensions = ">=3.7.4"
urllib3 = [
{version = ">=1.26.5", markers = "python_version >= \"3.12\" and python_version < \"4.0\""},
{version = ">=1.26.0", markers = "python_version >= \"3.8\" and python_version < \"3.12\""},
{version = ">=1.26.5", markers = "python_version >= \"3.12\" and python_version < \"4.0\""},
]
[package.extras]
@@ -4238,22 +4145,6 @@ files = [
[package.extras]
twisted = ["twisted"]
[[package]]
name = "prometheus-fastapi-instrumentator"
version = "7.1.0"
description = "Instrument your FastAPI app with Prometheus metrics"
optional = false
python-versions = ">=3.8"
groups = ["main"]
files = [
{file = "prometheus_fastapi_instrumentator-7.1.0-py3-none-any.whl", hash = "sha256:978130f3c0bb7b8ebcc90d35516a6fe13e02d2eb358c8f83887cdef7020c31e9"},
{file = "prometheus_fastapi_instrumentator-7.1.0.tar.gz", hash = "sha256:be7cd61eeea4e5912aeccb4261c6631b3f227d8924542d79eaf5af3f439cbe5e"},
]
[package.dependencies]
prometheus-client = ">=0.8.0,<1.0.0"
starlette = ">=0.30.0,<1.0.0"
[[package]]
name = "propcache"
version = "0.3.2"
@@ -5201,8 +5092,8 @@ files = [
grpcio = ">=1.41.0"
httpx = {version = ">=0.20.0", extras = ["http2"]}
numpy = [
{version = ">=2.1.0", markers = "python_version >= \"3.13\""},
{version = ">=1.21", markers = "python_version >= \"3.10\" and python_version < \"3.12\""},
{version = ">=2.1.0", markers = "python_version >= \"3.13\""},
{version = ">=1.26", markers = "python_version == \"3.12\""},
]
portalocker = ">=2.7.0,<3.0.0"
@@ -6297,7 +6188,7 @@ description = "A lil' TOML parser"
optional = false
python-versions = ">=3.8"
groups = ["main", "dev"]
markers = "python_version == \"3.10\""
markers = "python_version < \"3.11\""
files = [
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@@ -7252,4 +7143,4 @@ cffi = ["cffi (>=1.11)"]
[metadata]
lock-version = "2.1"
python-versions = ">=3.10,<3.14"
content-hash = "b2363edeebb91f410039c8d4b563f683c1edb0cf4bda4f3e6c287040e93639bc"
content-hash = "80d4dc2cbcd1ae33b2fa3920db5dcb1f82ad252d1e4a8bfeba8b2f2eebbdda0d"

View File

@@ -38,7 +38,6 @@ mem0ai = "^0.1.115"
moviepy = "^2.1.2"
ollama = "^0.5.1"
openai = "^1.97.1"
orjson = "^3.10.0"
pika = "^1.3.2"
pinecone = "^7.3.0"
poetry = "2.1.1" # CHECK DEPENDABOT SUPPORT BEFORE UPGRADING
@@ -46,7 +45,6 @@ postmarker = "^1.0"
praw = "~7.8.1"
prisma = "^0.15.0"
prometheus-client = "^0.22.1"
prometheus-fastapi-instrumentator = "^7.0.0"
psutil = "^7.0.0"
psycopg2-binary = "^2.9.10"
pydantic = { extras = ["email"], version = "^2.11.7" }

View File

@@ -110,7 +110,6 @@ model AgentGraph {
name String?
description String?
instructions String?
recommendedScheduleCron String?
isActive Boolean @default(true)
@@ -135,7 +134,7 @@ model AgentGraph {
StoreListingVersions StoreListingVersion[]
@@id(name: "graphVersionId", [id, version])
@@index([userId, isActive, id, version])
@@index([userId, isActive])
@@index([forkedFromId, forkedFromVersion])
}
@@ -371,16 +370,10 @@ model AgentGraphExecution {
stats Json?
// Sharing fields
isShared Boolean @default(false)
shareToken String? @unique
sharedAt DateTime?
@@index([agentGraphId, agentGraphVersion])
@@index([userId, isDeleted, createdAt])
@@index([userId])
@@index([createdAt])
@@index([agentPresetId])
@@index([shareToken])
}
// This model describes the execution of an AgentNode.
@@ -535,7 +528,7 @@ model CreditTransaction {
createdAt DateTime @default(now())
userId String
User User? @relation(fields: [userId], references: [id], onDelete: NoAction)
User User @relation(fields: [userId], references: [id], onDelete: Cascade)
amount Int
type CreditTransactionType
@@ -764,7 +757,6 @@ model StoreListingVersion {
videoUrl String?
imageUrls String[]
description String
instructions String?
categories String[]
isFeatured Boolean @default(false)

View File

@@ -11,7 +11,6 @@
"creator_avatar": "avatar1.jpg",
"sub_heading": "Test agent subheading",
"description": "Test agent description",
"instructions": null,
"categories": [
"category1",
"category2"

View File

@@ -1,5 +1,4 @@
{
"created_at": "2025-09-04T13:37:00",
"credentials_input_schema": {
"properties": {},
"title": "TestGraphCredentialsInputSchema",
@@ -15,7 +14,6 @@
"required": [],
"type": "object"
},
"instructions": null,
"is_active": true,
"links": [],
"name": "Test Graph",

View File

@@ -15,7 +15,6 @@
"required": [],
"type": "object"
},
"instructions": null,
"is_active": true,
"name": "Test Graph",
"output_schema": {

View File

@@ -11,7 +11,6 @@
"updated_at": "2023-01-01T00:00:00",
"name": "Test Agent 1",
"description": "Test Description 1",
"instructions": null,
"input_schema": {
"type": "object",
"properties": {}
@@ -29,7 +28,6 @@
"new_output": false,
"can_access_graph": true,
"is_latest_version": true,
"is_favorite": false,
"recommended_schedule_cron": null
},
{
@@ -43,7 +41,6 @@
"updated_at": "2023-01-01T00:00:00",
"name": "Test Agent 2",
"description": "Test Description 2",
"instructions": null,
"input_schema": {
"type": "object",
"properties": {}
@@ -61,7 +58,6 @@
"new_output": false,
"can_access_graph": false,
"is_latest_version": true,
"is_favorite": false,
"recommended_schedule_cron": null
}
],

View File

@@ -7,7 +7,6 @@
"sub_heading": "Test agent subheading",
"slug": "test-agent",
"description": "Test agent description",
"instructions": null,
"image_urls": [
"test.jpg"
],

View File

@@ -146,23 +146,16 @@ class TestAutoRegistry:
"""Test API key environment variable registration."""
import os
from backend.sdk.builder import ProviderBuilder
# Set up a test environment variable
os.environ["TEST_API_KEY"] = "test-api-key-value"
try:
# Use ProviderBuilder which calls register_api_key and creates the credential
(
ProviderBuilder("test_provider")
.with_api_key("TEST_API_KEY", "Test API Key")
.build()
)
AutoRegistry.register_api_key("test_provider", "TEST_API_KEY")
# Verify the mapping is stored
assert AutoRegistry._api_key_mappings["test_provider"] == "TEST_API_KEY"
# Verify a credential was created through the provider
# Verify a credential was created
all_creds = AutoRegistry.get_all_credentials()
test_cred = next(
(c for c in all_creds if c.id == "test_provider-default"), None

View File

@@ -37,7 +37,7 @@ services:
context: ../
dockerfile: autogpt_platform/backend/Dockerfile
target: migrate
command: ["sh", "-c", "poetry run prisma generate && poetry run prisma migrate deploy"]
command: ["sh", "-c", "poetry run prisma migrate deploy"]
develop:
watch:
- path: ./
@@ -65,6 +65,7 @@ services:
redis:
image: redis:latest
command: redis-server --requirepass password
ports:
- "6379:6379"
networks:

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