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2 Commits

Author SHA1 Message Date
Swifty
46c65cb567 pr comments 2026-02-09 14:46:21 +01:00
Swifty
17cafff60c fix(backend): Auto-fork marketplace agent on first save to fix "Graph not found" error
When a user adds a marketplace agent to their library and tries to save
edits, the update_graph endpoint returned 404 because the graph is owned
by the original creator. Now, if the user has the graph in their library
but doesn't own it, a fork is automatically created with their edits
applied, new IDs assigned, and a new library agent entry created.
2026-02-09 12:33:10 +01:00
427 changed files with 11178 additions and 20081 deletions

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@@ -22,7 +22,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
ref: ${{ github.event.workflow_run.head_branch }}
fetch-depth: 0

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@@ -30,7 +30,7 @@ jobs:
actions: read # Required for CI access
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 1

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@@ -40,7 +40,7 @@ jobs:
actions: read # Required for CI access
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 1

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@@ -58,7 +58,7 @@ jobs:
# your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
# Initializes the CodeQL tools for scanning.
- name: Initialize CodeQL

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@@ -27,7 +27,7 @@ jobs:
# If you do not check out your code, Copilot will do this for you.
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0
submodules: true

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@@ -23,7 +23,7 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 1

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@@ -23,7 +23,7 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0

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@@ -28,7 +28,7 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 1

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@@ -25,7 +25,7 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
ref: ${{ github.event.inputs.git_ref || github.ref_name }}
@@ -52,7 +52,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Trigger deploy workflow
uses: peter-evans/repository-dispatch@v4
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.DEPLOY_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

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@@ -17,7 +17,7 @@ jobs:
steps:
- name: Checkout code
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
ref: ${{ github.ref_name || 'master' }}
@@ -45,7 +45,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Trigger deploy workflow
uses: peter-evans/repository-dispatch@v4
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.DEPLOY_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

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@@ -68,7 +68,7 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0
submodules: true

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@@ -82,7 +82,7 @@ jobs:
- name: Dispatch Deploy Event
if: steps.check_status.outputs.should_deploy == 'true'
uses: peter-evans/repository-dispatch@v4
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.DISPATCH_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -110,7 +110,7 @@ jobs:
- name: Dispatch Undeploy Event (from comment)
if: steps.check_status.outputs.should_undeploy == 'true'
uses: peter-evans/repository-dispatch@v4
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.DISPATCH_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -168,7 +168,7 @@ jobs:
github.event_name == 'pull_request' &&
github.event.action == 'closed' &&
steps.check_pr_close.outputs.should_undeploy == 'true'
uses: peter-evans/repository-dispatch@v4
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.DISPATCH_TOKEN }}
repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

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@@ -31,7 +31,7 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Check for component changes
uses: dorny/paths-filter@v3
@@ -71,7 +71,7 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v6
@@ -107,7 +107,7 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
fetch-depth: 0
@@ -148,7 +148,7 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: recursive
@@ -277,7 +277,7 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: recursive

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@@ -29,7 +29,7 @@ jobs:
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v6
@@ -56,14 +56,14 @@ jobs:
run: pnpm install --frozen-lockfile
types:
runs-on: big-boi
runs-on: ubuntu-latest
needs: setup
strategy:
fail-fast: false
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: recursive
@@ -85,7 +85,7 @@ jobs:
- name: Run docker compose
run: |
docker compose -f ../docker-compose.yml --profile local up -d deps_backend
docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
- name: Restore dependencies cache
uses: actions/cache@v5

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@@ -11,7 +11,7 @@ jobs:
steps:
# - name: Wait some time for all actions to start
# run: sleep 30
- uses: actions/checkout@v6
- uses: actions/checkout@v4
# with:
# fetch-depth: 0
- name: Set up Python

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@@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand.
# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand.
[[package]]
name = "annotated-doc"
@@ -67,7 +67,7 @@ description = "Backport of asyncio.Runner, a context manager that controls event
optional = false
python-versions = "<3.11,>=3.8"
groups = ["dev"]
markers = "python_version < \"3.11\""
markers = "python_version == \"3.10\""
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@@ -326,118 +326,100 @@ files = [
[[package]]
name = "coverage"
version = "7.13.4"
version = "7.10.5"
description = "Code coverage measurement for Python"
optional = false
python-versions = ">=3.10"
python-versions = ">=3.9"
groups = ["dev"]
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{file = "coverage-7.10.5.tar.gz", hash = "sha256:f2e57716a78bc3ae80b2207be0709a3b2b63b9f2dcf9740ee6ac03588a2015b6"},
]
[package.dependencies]
@@ -541,7 +523,7 @@ description = "Backport of PEP 654 (exception groups)"
optional = false
python-versions = ">=3.7"
groups = ["main", "dev"]
markers = "python_version < \"3.11\""
markers = "python_version == \"3.10\""
files = [
{file = "exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10"},
{file = "exceptiongroup-1.3.0.tar.gz", hash = "sha256:b241f5885f560bc56a59ee63ca4c6a8bfa46ae4ad651af316d4e81817bb9fd88"},
@@ -2180,23 +2162,23 @@ testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
[[package]]
name = "pytest-cov"
version = "7.0.0"
version = "6.2.1"
description = "Pytest plugin for measuring coverage."
optional = false
python-versions = ">=3.9"
groups = ["dev"]
files = [
{file = "pytest_cov-7.0.0-py3-none-any.whl", hash = "sha256:3b8e9558b16cc1479da72058bdecf8073661c7f57f7d3c5f22a1c23507f2d861"},
{file = "pytest_cov-7.0.0.tar.gz", hash = "sha256:33c97eda2e049a0c5298e91f519302a1334c26ac65c1a483d6206fd458361af1"},
{file = "pytest_cov-6.2.1-py3-none-any.whl", hash = "sha256:f5bc4c23f42f1cdd23c70b1dab1bbaef4fc505ba950d53e0081d0730dd7e86d5"},
{file = "pytest_cov-6.2.1.tar.gz", hash = "sha256:25cc6cc0a5358204b8108ecedc51a9b57b34cc6b8c967cc2c01a4e00d8a67da2"},
]
[package.dependencies]
coverage = {version = ">=7.10.6", extras = ["toml"]}
coverage = {version = ">=7.5", extras = ["toml"]}
pluggy = ">=1.2"
pytest = ">=7"
pytest = ">=6.2.5"
[package.extras]
testing = ["process-tests", "pytest-xdist", "virtualenv"]
testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"]
[[package]]
name = "pytest-mock"
@@ -2563,7 +2545,7 @@ description = "A lil' TOML parser"
optional = false
python-versions = ">=3.8"
groups = ["dev"]
markers = "python_version < \"3.11\""
markers = "python_version == \"3.10\""
files = [
{file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"},
{file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"},
@@ -2911,4 +2893,4 @@ type = ["pytest-mypy"]
[metadata]
lock-version = "2.1"
python-versions = ">=3.10,<4.0"
content-hash = "40eae94995dc0a388fa832ed4af9b6137f28d5b5ced3aaea70d5f91d4d9a179d"
content-hash = "b7ac335a86aa44c3d7d2802298818b389a6f1286e3e9b7b0edb2ff06377cecaf"

View File

@@ -26,7 +26,7 @@ pyright = "^1.1.408"
pytest = "^8.4.1"
pytest-asyncio = "^1.3.0"
pytest-mock = "^3.15.1"
pytest-cov = "^7.0.0"
pytest-cov = "^6.2.1"
ruff = "^0.15.0"
[build-system]

View File

@@ -10,7 +10,7 @@ from typing_extensions import TypedDict
import backend.api.features.store.cache as store_cache
import backend.api.features.store.model as store_model
import backend.blocks
import backend.data.block
from backend.api.external.middleware import require_permission
from backend.data import execution as execution_db
from backend.data import graph as graph_db
@@ -67,7 +67,7 @@ async def get_user_info(
dependencies=[Security(require_permission(APIKeyPermission.READ_BLOCK))],
)
async def get_graph_blocks() -> Sequence[dict[Any, Any]]:
blocks = [block() for block in backend.blocks.get_blocks().values()]
blocks = [block() for block in backend.data.block.get_blocks().values()]
return [b.to_dict() for b in blocks if not b.disabled]
@@ -83,7 +83,7 @@ async def execute_graph_block(
require_permission(APIKeyPermission.EXECUTE_BLOCK)
),
) -> CompletedBlockOutput:
obj = backend.blocks.get_block(block_id)
obj = backend.data.block.get_block(block_id)
if not obj:
raise HTTPException(status_code=404, detail=f"Block #{block_id} not found.")
if obj.disabled:

View File

@@ -10,15 +10,10 @@ import backend.api.features.library.db as library_db
import backend.api.features.library.model as library_model
import backend.api.features.store.db as store_db
import backend.api.features.store.model as store_model
import backend.data.block
from backend.blocks import load_all_blocks
from backend.blocks._base import (
AnyBlockSchema,
BlockCategory,
BlockInfo,
BlockSchema,
BlockType,
)
from backend.blocks.llm import LlmModel
from backend.data.block import AnyBlockSchema, BlockCategory, BlockInfo, BlockSchema
from backend.data.db import query_raw_with_schema
from backend.integrations.providers import ProviderName
from backend.util.cache import cached
@@ -27,7 +22,7 @@ from backend.util.models import Pagination
from .model import (
BlockCategoryResponse,
BlockResponse,
BlockTypeFilter,
BlockType,
CountResponse,
FilterType,
Provider,
@@ -93,7 +88,7 @@ def get_block_categories(category_blocks: int = 3) -> list[BlockCategoryResponse
def get_blocks(
*,
category: str | None = None,
type: BlockTypeFilter | None = None,
type: BlockType | None = None,
provider: ProviderName | None = None,
page: int = 1,
page_size: int = 50,
@@ -674,9 +669,9 @@ async def get_suggested_blocks(count: int = 5) -> list[BlockInfo]:
for block_type in load_all_blocks().values():
block: AnyBlockSchema = block_type()
if block.disabled or block.block_type in (
BlockType.INPUT,
BlockType.OUTPUT,
BlockType.AGENT,
backend.data.block.BlockType.INPUT,
backend.data.block.BlockType.OUTPUT,
backend.data.block.BlockType.AGENT,
):
continue
# Find the execution count for this block

View File

@@ -4,7 +4,7 @@ from pydantic import BaseModel
import backend.api.features.library.model as library_model
import backend.api.features.store.model as store_model
from backend.blocks._base import BlockInfo
from backend.data.block import BlockInfo
from backend.integrations.providers import ProviderName
from backend.util.models import Pagination
@@ -15,7 +15,7 @@ FilterType = Literal[
"my_agents",
]
BlockTypeFilter = Literal["all", "input", "action", "output"]
BlockType = Literal["all", "input", "action", "output"]
class SearchEntry(BaseModel):

View File

@@ -88,7 +88,7 @@ async def get_block_categories(
)
async def get_blocks(
category: Annotated[str | None, fastapi.Query()] = None,
type: Annotated[builder_model.BlockTypeFilter | None, fastapi.Query()] = None,
type: Annotated[builder_model.BlockType | None, fastapi.Query()] = None,
provider: Annotated[ProviderName | None, fastapi.Query()] = None,
page: Annotated[int, fastapi.Query()] = 1,
page_size: Annotated[int, fastapi.Query()] = 50,

View File

@@ -93,12 +93,6 @@ class ChatConfig(BaseSettings):
description="Name of the prompt in Langfuse to fetch",
)
# Extended thinking configuration for Claude models
thinking_enabled: bool = Field(
default=True,
description="Enable adaptive thinking for Claude models via OpenRouter",
)
@field_validator("api_key", mode="before")
@classmethod
def get_api_key(cls, v):

View File

@@ -45,7 +45,10 @@ async def create_chat_session(
successfulAgentRuns=SafeJson({}),
successfulAgentSchedules=SafeJson({}),
)
return await PrismaChatSession.prisma().create(data=data)
return await PrismaChatSession.prisma().create(
data=data,
include={"Messages": True},
)
async def update_chat_session(

View File

@@ -2,7 +2,7 @@ import asyncio
import logging
import uuid
from datetime import UTC, datetime
from typing import Any, cast
from typing import Any
from weakref import WeakValueDictionary
from openai.types.chat import (
@@ -104,26 +104,6 @@ class ChatSession(BaseModel):
successful_agent_runs: dict[str, int] = {}
successful_agent_schedules: dict[str, int] = {}
def add_tool_call_to_current_turn(self, tool_call: dict) -> None:
"""Attach a tool_call to the current turn's assistant message.
Searches backwards for the most recent assistant message (stopping at
any user message boundary). If found, appends the tool_call to it.
Otherwise creates a new assistant message with the tool_call.
"""
for msg in reversed(self.messages):
if msg.role == "user":
break
if msg.role == "assistant":
if not msg.tool_calls:
msg.tool_calls = []
msg.tool_calls.append(tool_call)
return
self.messages.append(
ChatMessage(role="assistant", content="", tool_calls=[tool_call])
)
@staticmethod
def new(user_id: str) -> "ChatSession":
return ChatSession(
@@ -192,47 +172,6 @@ class ChatSession(BaseModel):
successful_agent_schedules=successful_agent_schedules,
)
@staticmethod
def _merge_consecutive_assistant_messages(
messages: list[ChatCompletionMessageParam],
) -> list[ChatCompletionMessageParam]:
"""Merge consecutive assistant messages into single messages.
Long-running tool flows can create split assistant messages: one with
text content and another with tool_calls. Anthropic's API requires
tool_result blocks to reference a tool_use in the immediately preceding
assistant message, so these splits cause 400 errors via OpenRouter.
"""
if len(messages) < 2:
return messages
result: list[ChatCompletionMessageParam] = [messages[0]]
for msg in messages[1:]:
prev = result[-1]
if prev.get("role") != "assistant" or msg.get("role") != "assistant":
result.append(msg)
continue
prev = cast(ChatCompletionAssistantMessageParam, prev)
curr = cast(ChatCompletionAssistantMessageParam, msg)
curr_content = curr.get("content") or ""
if curr_content:
prev_content = prev.get("content") or ""
prev["content"] = (
f"{prev_content}\n{curr_content}" if prev_content else curr_content
)
curr_tool_calls = curr.get("tool_calls")
if curr_tool_calls:
prev_tool_calls = prev.get("tool_calls")
prev["tool_calls"] = (
list(prev_tool_calls) + list(curr_tool_calls)
if prev_tool_calls
else list(curr_tool_calls)
)
return result
def to_openai_messages(self) -> list[ChatCompletionMessageParam]:
messages = []
for message in self.messages:
@@ -319,7 +258,7 @@ class ChatSession(BaseModel):
name=message.name or "",
)
)
return self._merge_consecutive_assistant_messages(messages)
return messages
async def _get_session_from_cache(session_id: str) -> ChatSession | None:

View File

@@ -1,16 +1,4 @@
from typing import cast
import pytest
from openai.types.chat import (
ChatCompletionAssistantMessageParam,
ChatCompletionMessageParam,
ChatCompletionToolMessageParam,
ChatCompletionUserMessageParam,
)
from openai.types.chat.chat_completion_message_tool_call_param import (
ChatCompletionMessageToolCallParam,
Function,
)
from .model import (
ChatMessage,
@@ -129,205 +117,3 @@ async def test_chatsession_db_storage(setup_test_user, test_user_id):
loaded.tool_calls is not None
), f"Tool calls missing for {orig.role} message"
assert len(orig.tool_calls) == len(loaded.tool_calls)
# --------------------------------------------------------------------------- #
# _merge_consecutive_assistant_messages #
# --------------------------------------------------------------------------- #
_tc = ChatCompletionMessageToolCallParam(
id="tc1", type="function", function=Function(name="do_stuff", arguments="{}")
)
_tc2 = ChatCompletionMessageToolCallParam(
id="tc2", type="function", function=Function(name="other", arguments="{}")
)
def test_merge_noop_when_no_consecutive_assistants():
"""Messages without consecutive assistants are returned unchanged."""
msgs = [
ChatCompletionUserMessageParam(role="user", content="hi"),
ChatCompletionAssistantMessageParam(role="assistant", content="hello"),
ChatCompletionUserMessageParam(role="user", content="bye"),
]
merged = ChatSession._merge_consecutive_assistant_messages(msgs)
assert len(merged) == 3
assert [m["role"] for m in merged] == ["user", "assistant", "user"]
def test_merge_splits_text_and_tool_calls():
"""The exact bug scenario: text-only assistant followed by tool_calls-only assistant."""
msgs = [
ChatCompletionUserMessageParam(role="user", content="build agent"),
ChatCompletionAssistantMessageParam(
role="assistant", content="Let me build that"
),
ChatCompletionAssistantMessageParam(
role="assistant", content="", tool_calls=[_tc]
),
ChatCompletionToolMessageParam(role="tool", content="ok", tool_call_id="tc1"),
]
merged = ChatSession._merge_consecutive_assistant_messages(msgs)
assert len(merged) == 3
assert merged[0]["role"] == "user"
assert merged[2]["role"] == "tool"
a = cast(ChatCompletionAssistantMessageParam, merged[1])
assert a["role"] == "assistant"
assert a.get("content") == "Let me build that"
assert a.get("tool_calls") == [_tc]
def test_merge_combines_tool_calls_from_both():
"""Both consecutive assistants have tool_calls — they get merged."""
msgs: list[ChatCompletionAssistantMessageParam] = [
ChatCompletionAssistantMessageParam(
role="assistant", content="text", tool_calls=[_tc]
),
ChatCompletionAssistantMessageParam(
role="assistant", content="", tool_calls=[_tc2]
),
]
merged = ChatSession._merge_consecutive_assistant_messages(msgs) # type: ignore[arg-type]
assert len(merged) == 1
a = cast(ChatCompletionAssistantMessageParam, merged[0])
assert a.get("tool_calls") == [_tc, _tc2]
assert a.get("content") == "text"
def test_merge_three_consecutive_assistants():
"""Three consecutive assistants collapse into one."""
msgs: list[ChatCompletionAssistantMessageParam] = [
ChatCompletionAssistantMessageParam(role="assistant", content="a"),
ChatCompletionAssistantMessageParam(role="assistant", content="b"),
ChatCompletionAssistantMessageParam(
role="assistant", content="", tool_calls=[_tc]
),
]
merged = ChatSession._merge_consecutive_assistant_messages(msgs) # type: ignore[arg-type]
assert len(merged) == 1
a = cast(ChatCompletionAssistantMessageParam, merged[0])
assert a.get("content") == "a\nb"
assert a.get("tool_calls") == [_tc]
def test_merge_empty_and_single_message():
"""Edge cases: empty list and single message."""
assert ChatSession._merge_consecutive_assistant_messages([]) == []
single: list[ChatCompletionMessageParam] = [
ChatCompletionUserMessageParam(role="user", content="hi")
]
assert ChatSession._merge_consecutive_assistant_messages(single) == single
# --------------------------------------------------------------------------- #
# add_tool_call_to_current_turn #
# --------------------------------------------------------------------------- #
_raw_tc = {
"id": "tc1",
"type": "function",
"function": {"name": "f", "arguments": "{}"},
}
_raw_tc2 = {
"id": "tc2",
"type": "function",
"function": {"name": "g", "arguments": "{}"},
}
def test_add_tool_call_appends_to_existing_assistant():
"""When the last assistant is from the current turn, tool_call is added to it."""
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="hi"),
ChatMessage(role="assistant", content="working on it"),
]
session.add_tool_call_to_current_turn(_raw_tc)
assert len(session.messages) == 2 # no new message created
assert session.messages[1].tool_calls == [_raw_tc]
def test_add_tool_call_creates_assistant_when_none_exists():
"""When there's no current-turn assistant, a new one is created."""
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="hi"),
]
session.add_tool_call_to_current_turn(_raw_tc)
assert len(session.messages) == 2
assert session.messages[1].role == "assistant"
assert session.messages[1].tool_calls == [_raw_tc]
def test_add_tool_call_does_not_cross_user_boundary():
"""A user message acts as a boundary — previous assistant is not modified."""
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="assistant", content="old turn"),
ChatMessage(role="user", content="new message"),
]
session.add_tool_call_to_current_turn(_raw_tc)
assert len(session.messages) == 3 # new assistant was created
assert session.messages[0].tool_calls is None # old assistant untouched
assert session.messages[2].role == "assistant"
assert session.messages[2].tool_calls == [_raw_tc]
def test_add_tool_call_multiple_times():
"""Multiple long-running tool calls accumulate on the same assistant."""
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="hi"),
ChatMessage(role="assistant", content="doing stuff"),
]
session.add_tool_call_to_current_turn(_raw_tc)
# Simulate a pending tool result in between (like _yield_tool_call does)
session.messages.append(
ChatMessage(role="tool", content="pending", tool_call_id="tc1")
)
session.add_tool_call_to_current_turn(_raw_tc2)
assert len(session.messages) == 3 # user, assistant, tool — no extra assistant
assert session.messages[1].tool_calls == [_raw_tc, _raw_tc2]
def test_to_openai_messages_merges_split_assistants():
"""End-to-end: session with split assistants produces valid OpenAI messages."""
session = ChatSession.new(user_id="u")
session.messages = [
ChatMessage(role="user", content="build agent"),
ChatMessage(role="assistant", content="Let me build that"),
ChatMessage(
role="assistant",
content="",
tool_calls=[
{
"id": "tc1",
"type": "function",
"function": {"name": "create_agent", "arguments": "{}"},
}
],
),
ChatMessage(role="tool", content="done", tool_call_id="tc1"),
ChatMessage(role="assistant", content="Saved!"),
ChatMessage(role="user", content="show me an example run"),
]
openai_msgs = session.to_openai_messages()
# The two consecutive assistants at index 1,2 should be merged
roles = [m["role"] for m in openai_msgs]
assert roles == ["user", "assistant", "tool", "assistant", "user"]
# The merged assistant should have both content and tool_calls
merged = cast(ChatCompletionAssistantMessageParam, openai_msgs[1])
assert merged.get("content") == "Let me build that"
tc_list = merged.get("tool_calls")
assert tc_list is not None and len(list(tc_list)) == 1
assert list(tc_list)[0]["id"] == "tc1"

View File

@@ -10,8 +10,6 @@ from typing import Any
from pydantic import BaseModel, Field
from backend.util.json import dumps as json_dumps
class ResponseType(str, Enum):
"""Types of streaming responses following AI SDK protocol."""
@@ -20,10 +18,6 @@ class ResponseType(str, Enum):
START = "start"
FINISH = "finish"
# Step lifecycle (one LLM API call within a message)
START_STEP = "start-step"
FINISH_STEP = "finish-step"
# Text streaming
TEXT_START = "text-start"
TEXT_DELTA = "text-delta"
@@ -63,16 +57,6 @@ class StreamStart(StreamBaseResponse):
description="Task ID for SSE reconnection. Clients can reconnect using GET /tasks/{taskId}/stream",
)
def to_sse(self) -> str:
"""Convert to SSE format, excluding non-protocol fields like taskId."""
import json
data: dict[str, Any] = {
"type": self.type.value,
"messageId": self.messageId,
}
return f"data: {json.dumps(data)}\n\n"
class StreamFinish(StreamBaseResponse):
"""End of message/stream."""
@@ -80,26 +64,6 @@ class StreamFinish(StreamBaseResponse):
type: ResponseType = ResponseType.FINISH
class StreamStartStep(StreamBaseResponse):
"""Start of a step (one LLM API call within a message).
The AI SDK uses this to add a step-start boundary to message.parts,
enabling visual separation between multiple LLM calls in a single message.
"""
type: ResponseType = ResponseType.START_STEP
class StreamFinishStep(StreamBaseResponse):
"""End of a step (one LLM API call within a message).
The AI SDK uses this to reset activeTextParts and activeReasoningParts,
so the next LLM call in a tool-call continuation starts with clean state.
"""
type: ResponseType = ResponseType.FINISH_STEP
# ========== Text Streaming ==========
@@ -153,7 +117,7 @@ class StreamToolOutputAvailable(StreamBaseResponse):
type: ResponseType = ResponseType.TOOL_OUTPUT_AVAILABLE
toolCallId: str = Field(..., description="Tool call ID this responds to")
output: str | dict[str, Any] = Field(..., description="Tool execution output")
# Keep these for internal backend use
# Additional fields for internal use (not part of AI SDK spec but useful)
toolName: str | None = Field(
default=None, description="Name of the tool that was executed"
)
@@ -161,17 +125,6 @@ class StreamToolOutputAvailable(StreamBaseResponse):
default=True, description="Whether the tool execution succeeded"
)
def to_sse(self) -> str:
"""Convert to SSE format, excluding non-spec fields."""
import json
data = {
"type": self.type.value,
"toolCallId": self.toolCallId,
"output": self.output,
}
return f"data: {json.dumps(data)}\n\n"
# ========== Other ==========
@@ -195,18 +148,6 @@ class StreamError(StreamBaseResponse):
default=None, description="Additional error details"
)
def to_sse(self) -> str:
"""Convert to SSE format, only emitting fields required by AI SDK protocol.
The AI SDK uses z.strictObject({type, errorText}) which rejects
any extra fields like `code` or `details`.
"""
data = {
"type": self.type.value,
"errorText": self.errorText,
}
return f"data: {json_dumps(data)}\n\n"
class StreamHeartbeat(StreamBaseResponse):
"""Heartbeat to keep SSE connection alive during long-running operations.

View File

@@ -6,7 +6,7 @@ from collections.abc import AsyncGenerator
from typing import Annotated
from autogpt_libs import auth
from fastapi import APIRouter, Depends, Header, HTTPException, Query, Response, Security
from fastapi import APIRouter, Depends, Header, HTTPException, Query, Security
from fastapi.responses import StreamingResponse
from pydantic import BaseModel
@@ -17,29 +17,7 @@ from . import stream_registry
from .completion_handler import process_operation_failure, process_operation_success
from .config import ChatConfig
from .model import ChatSession, create_chat_session, get_chat_session, get_user_sessions
from .response_model import StreamFinish, StreamHeartbeat
from .tools.models import (
AgentDetailsResponse,
AgentOutputResponse,
AgentPreviewResponse,
AgentSavedResponse,
AgentsFoundResponse,
BlockListResponse,
BlockOutputResponse,
ClarificationNeededResponse,
DocPageResponse,
DocSearchResultsResponse,
ErrorResponse,
ExecutionStartedResponse,
InputValidationErrorResponse,
NeedLoginResponse,
NoResultsResponse,
OperationInProgressResponse,
OperationPendingResponse,
OperationStartedResponse,
SetupRequirementsResponse,
UnderstandingUpdatedResponse,
)
from .response_model import StreamFinish, StreamHeartbeat, StreamStart
config = ChatConfig()
@@ -288,36 +266,12 @@ async def stream_chat_post(
"""
import asyncio
import time
stream_start_time = time.perf_counter()
log_meta = {"component": "ChatStream", "session_id": session_id}
if user_id:
log_meta["user_id"] = user_id
logger.info(
f"[TIMING] stream_chat_post STARTED, session={session_id}, "
f"user={user_id}, message_len={len(request.message)}",
extra={"json_fields": log_meta},
)
session = await _validate_and_get_session(session_id, user_id)
logger.info(
f"[TIMING] session validated in {(time.perf_counter() - stream_start_time)*1000:.1f}ms",
extra={
"json_fields": {
**log_meta,
"duration_ms": (time.perf_counter() - stream_start_time) * 1000,
}
},
)
# Create a task in the stream registry for reconnection support
task_id = str(uuid_module.uuid4())
operation_id = str(uuid_module.uuid4())
log_meta["task_id"] = task_id
task_create_start = time.perf_counter()
await stream_registry.create_task(
task_id=task_id,
session_id=session_id,
@@ -326,28 +280,14 @@ async def stream_chat_post(
tool_name="chat",
operation_id=operation_id,
)
logger.info(
f"[TIMING] create_task completed in {(time.perf_counter() - task_create_start)*1000:.1f}ms",
extra={
"json_fields": {
**log_meta,
"duration_ms": (time.perf_counter() - task_create_start) * 1000,
}
},
)
# Background task that runs the AI generation independently of SSE connection
async def run_ai_generation():
import time as time_module
gen_start_time = time_module.perf_counter()
logger.info(
f"[TIMING] run_ai_generation STARTED, task={task_id}, session={session_id}, user={user_id}",
extra={"json_fields": log_meta},
)
first_chunk_time, ttfc = None, None
chunk_count = 0
try:
# Emit a start event with task_id for reconnection
start_chunk = StreamStart(messageId=task_id, taskId=task_id)
await stream_registry.publish_chunk(task_id, start_chunk)
async for chunk in chat_service.stream_chat_completion(
session_id,
request.message,
@@ -355,79 +295,25 @@ async def stream_chat_post(
user_id=user_id,
session=session, # Pass pre-fetched session to avoid double-fetch
context=request.context,
_task_id=task_id, # Pass task_id so service emits start with taskId for reconnection
):
chunk_count += 1
if first_chunk_time is None:
first_chunk_time = time_module.perf_counter()
ttfc = first_chunk_time - gen_start_time
logger.info(
f"[TIMING] FIRST AI CHUNK at {ttfc:.2f}s, type={type(chunk).__name__}",
extra={
"json_fields": {
**log_meta,
"chunk_type": type(chunk).__name__,
"time_to_first_chunk_ms": ttfc * 1000,
}
},
)
# Write to Redis (subscribers will receive via XREAD)
await stream_registry.publish_chunk(task_id, chunk)
gen_end_time = time_module.perf_counter()
total_time = (gen_end_time - gen_start_time) * 1000
logger.info(
f"[TIMING] run_ai_generation FINISHED in {total_time/1000:.1f}s; "
f"task={task_id}, session={session_id}, "
f"ttfc={ttfc or -1:.2f}s, n_chunks={chunk_count}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"time_to_first_chunk_ms": (
ttfc * 1000 if ttfc is not None else None
),
"n_chunks": chunk_count,
}
},
)
# Mark task as completed
await stream_registry.mark_task_completed(task_id, "completed")
except Exception as e:
elapsed = time_module.perf_counter() - gen_start_time
logger.error(
f"[TIMING] run_ai_generation ERROR after {elapsed:.2f}s: {e}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed * 1000,
"error": str(e),
}
},
f"Error in background AI generation for session {session_id}: {e}"
)
await stream_registry.mark_task_completed(task_id, "failed")
# Start the AI generation in a background task
bg_task = asyncio.create_task(run_ai_generation())
await stream_registry.set_task_asyncio_task(task_id, bg_task)
setup_time = (time.perf_counter() - stream_start_time) * 1000
logger.info(
f"[TIMING] Background task started, setup={setup_time:.1f}ms",
extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
)
# SSE endpoint that subscribes to the task's stream
async def event_generator() -> AsyncGenerator[str, None]:
import time as time_module
event_gen_start = time_module.perf_counter()
logger.info(
f"[TIMING] event_generator STARTED, task={task_id}, session={session_id}, "
f"user={user_id}",
extra={"json_fields": log_meta},
)
subscriber_queue = None
first_chunk_yielded = False
chunks_yielded = 0
try:
# Subscribe to the task stream (this replays existing messages + live updates)
subscriber_queue = await stream_registry.subscribe_to_task(
@@ -442,70 +328,22 @@ async def stream_chat_post(
return
# Read from the subscriber queue and yield to SSE
logger.info(
"[TIMING] Starting to read from subscriber_queue",
extra={"json_fields": log_meta},
)
while True:
try:
chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
chunks_yielded += 1
if not first_chunk_yielded:
first_chunk_yielded = True
elapsed = time_module.perf_counter() - event_gen_start
logger.info(
f"[TIMING] FIRST CHUNK from queue at {elapsed:.2f}s, "
f"type={type(chunk).__name__}",
extra={
"json_fields": {
**log_meta,
"chunk_type": type(chunk).__name__,
"elapsed_ms": elapsed * 1000,
}
},
)
yield chunk.to_sse()
# Check for finish signal
if isinstance(chunk, StreamFinish):
total_time = time_module.perf_counter() - event_gen_start
logger.info(
f"[TIMING] StreamFinish received in {total_time:.2f}s; "
f"n_chunks={chunks_yielded}",
extra={
"json_fields": {
**log_meta,
"chunks_yielded": chunks_yielded,
"total_time_ms": total_time * 1000,
}
},
)
break
except asyncio.TimeoutError:
# Send heartbeat to keep connection alive
yield StreamHeartbeat().to_sse()
except GeneratorExit:
logger.info(
f"[TIMING] GeneratorExit (client disconnected), chunks={chunks_yielded}",
extra={
"json_fields": {
**log_meta,
"chunks_yielded": chunks_yielded,
"reason": "client_disconnect",
}
},
)
pass # Client disconnected - background task continues
except Exception as e:
elapsed = (time_module.perf_counter() - event_gen_start) * 1000
logger.error(
f"[TIMING] event_generator ERROR after {elapsed:.1f}ms: {e}",
extra={
"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}
},
)
logger.error(f"Error in SSE stream for task {task_id}: {e}")
finally:
# Unsubscribe when client disconnects or stream ends to prevent resource leak
if subscriber_queue is not None:
@@ -519,18 +357,6 @@ async def stream_chat_post(
exc_info=True,
)
# AI SDK protocol termination - always yield even if unsubscribe fails
total_time = time_module.perf_counter() - event_gen_start
logger.info(
f"[TIMING] event_generator FINISHED in {total_time:.2f}s; "
f"task={task_id}, session={session_id}, n_chunks={chunks_yielded}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time * 1000,
"chunks_yielded": chunks_yielded,
}
},
)
yield "data: [DONE]\n\n"
return StreamingResponse(
@@ -548,90 +374,63 @@ async def stream_chat_post(
@router.get(
"/sessions/{session_id}/stream",
)
async def resume_session_stream(
async def stream_chat_get(
session_id: str,
message: Annotated[str, Query(min_length=1, max_length=10000)],
user_id: str | None = Depends(auth.get_user_id),
is_user_message: bool = Query(default=True),
):
"""
Resume an active stream for a session.
Stream chat responses for a session (GET - legacy endpoint).
Called by the AI SDK's ``useChat(resume: true)`` on page load.
Checks for an active (in-progress) task on the session and either replays
the full SSE stream or returns 204 No Content if nothing is running.
Streams the AI/completion responses in real time over Server-Sent Events (SSE), including:
- Text fragments as they are generated
- Tool call UI elements (if invoked)
- Tool execution results
Args:
session_id: The chat session identifier.
session_id: The chat session identifier to associate with the streamed messages.
message: The user's new message to process.
user_id: Optional authenticated user ID.
is_user_message: Whether the message is a user message.
Returns:
StreamingResponse (SSE) when an active stream exists,
or 204 No Content when there is nothing to resume.
StreamingResponse: SSE-formatted response chunks.
"""
import asyncio
active_task, _last_id = await stream_registry.get_active_task_for_session(
session_id, user_id
)
if not active_task:
return Response(status_code=204)
subscriber_queue = await stream_registry.subscribe_to_task(
task_id=active_task.task_id,
user_id=user_id,
last_message_id="0-0", # Full replay so useChat rebuilds the message
)
if subscriber_queue is None:
return Response(status_code=204)
session = await _validate_and_get_session(session_id, user_id)
async def event_generator() -> AsyncGenerator[str, None]:
chunk_count = 0
first_chunk_type: str | None = None
try:
while True:
try:
chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
if chunk_count < 3:
logger.info(
"Resume stream chunk",
extra={
"session_id": session_id,
"chunk_type": str(chunk.type),
},
)
if not first_chunk_type:
first_chunk_type = str(chunk.type)
chunk_count += 1
yield chunk.to_sse()
if isinstance(chunk, StreamFinish):
break
except asyncio.TimeoutError:
yield StreamHeartbeat().to_sse()
except GeneratorExit:
pass
except Exception as e:
logger.error(f"Error in resume stream for session {session_id}: {e}")
finally:
try:
await stream_registry.unsubscribe_from_task(
active_task.task_id, subscriber_queue
async for chunk in chat_service.stream_chat_completion(
session_id,
message,
is_user_message=is_user_message,
user_id=user_id,
session=session, # Pass pre-fetched session to avoid double-fetch
):
if chunk_count < 3:
logger.info(
"Chat stream chunk",
extra={
"session_id": session_id,
"chunk_type": str(chunk.type),
},
)
except Exception as unsub_err:
logger.error(
f"Error unsubscribing from task {active_task.task_id}: {unsub_err}",
exc_info=True,
)
logger.info(
"Resume stream completed",
extra={
"session_id": session_id,
"n_chunks": chunk_count,
"first_chunk_type": first_chunk_type,
},
)
yield "data: [DONE]\n\n"
if not first_chunk_type:
first_chunk_type = str(chunk.type)
chunk_count += 1
yield chunk.to_sse()
logger.info(
"Chat stream completed",
extra={
"session_id": session_id,
"chunk_count": chunk_count,
"first_chunk_type": first_chunk_type,
},
)
# AI SDK protocol termination
yield "data: [DONE]\n\n"
return StreamingResponse(
event_generator(),
@@ -639,8 +438,8 @@ async def resume_session_stream(
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
"x-vercel-ai-ui-message-stream": "v1",
"X-Accel-Buffering": "no", # Disable nginx buffering
"x-vercel-ai-ui-message-stream": "v1", # AI SDK protocol header
},
)
@@ -952,42 +751,3 @@ async def health_check() -> dict:
"service": "chat",
"version": "0.1.0",
}
# ========== Schema Export (for OpenAPI / Orval codegen) ==========
ToolResponseUnion = (
AgentsFoundResponse
| NoResultsResponse
| AgentDetailsResponse
| SetupRequirementsResponse
| ExecutionStartedResponse
| NeedLoginResponse
| ErrorResponse
| InputValidationErrorResponse
| AgentOutputResponse
| UnderstandingUpdatedResponse
| AgentPreviewResponse
| AgentSavedResponse
| ClarificationNeededResponse
| BlockListResponse
| BlockOutputResponse
| DocSearchResultsResponse
| DocPageResponse
| OperationStartedResponse
| OperationPendingResponse
| OperationInProgressResponse
)
@router.get(
"/schema/tool-responses",
response_model=ToolResponseUnion,
include_in_schema=True,
summary="[Dummy] Tool response type export for codegen",
description="This endpoint is not meant to be called. It exists solely to "
"expose tool response models in the OpenAPI schema for frontend codegen.",
)
async def _tool_response_schema() -> ToolResponseUnion: # type: ignore[return]
"""Never called at runtime. Exists only so Orval generates TS types."""
raise HTTPException(status_code=501, detail="Schema-only endpoint")

View File

@@ -52,10 +52,8 @@ from .response_model import (
StreamBaseResponse,
StreamError,
StreamFinish,
StreamFinishStep,
StreamHeartbeat,
StreamStart,
StreamStartStep,
StreamTextDelta,
StreamTextEnd,
StreamTextStart,
@@ -353,10 +351,6 @@ async def stream_chat_completion(
retry_count: int = 0,
session: ChatSession | None = None,
context: dict[str, str] | None = None, # {url: str, content: str}
_continuation_message_id: (
str | None
) = None, # Internal: reuse message ID for tool call continuations
_task_id: str | None = None, # Internal: task ID for SSE reconnection support
) -> AsyncGenerator[StreamBaseResponse, None]:
"""Main entry point for streaming chat completions with database handling.
@@ -377,45 +371,21 @@ async def stream_chat_completion(
ValueError: If max_context_messages is exceeded
"""
completion_start = time.monotonic()
# Build log metadata for structured logging
log_meta = {"component": "ChatService", "session_id": session_id}
if user_id:
log_meta["user_id"] = user_id
logger.info(
f"[TIMING] stream_chat_completion STARTED, session={session_id}, user={user_id}, "
f"message_len={len(message) if message else 0}, is_user={is_user_message}",
extra={
"json_fields": {
**log_meta,
"message_len": len(message) if message else 0,
"is_user_message": is_user_message,
}
},
f"Streaming chat completion for session {session_id} for message {message} and user id {user_id}. Message is user message: {is_user_message}"
)
# Only fetch from Redis if session not provided (initial call)
if session is None:
fetch_start = time.monotonic()
session = await get_chat_session(session_id, user_id)
fetch_time = (time.monotonic() - fetch_start) * 1000
logger.info(
f"[TIMING] get_chat_session took {fetch_time:.1f}ms, "
f"n_messages={len(session.messages) if session else 0}",
extra={
"json_fields": {
**log_meta,
"duration_ms": fetch_time,
"n_messages": len(session.messages) if session else 0,
}
},
f"Fetched session from Redis: {session.session_id if session else 'None'}, "
f"message_count={len(session.messages) if session else 0}"
)
else:
logger.info(
f"[TIMING] Using provided session, messages={len(session.messages)}",
extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
f"Using provided session object: {session.session_id}, "
f"message_count={len(session.messages)}"
)
if not session:
@@ -436,25 +406,17 @@ async def stream_chat_completion(
# Track user message in PostHog
if is_user_message:
posthog_start = time.monotonic()
track_user_message(
user_id=user_id,
session_id=session_id,
message_length=len(message),
)
posthog_time = (time.monotonic() - posthog_start) * 1000
logger.info(
f"[TIMING] track_user_message took {posthog_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": posthog_time}},
)
upsert_start = time.monotonic()
session = await upsert_chat_session(session)
upsert_time = (time.monotonic() - upsert_start) * 1000
logger.info(
f"[TIMING] upsert_chat_session took {upsert_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": upsert_time}},
f"Upserting session: {session.session_id} with user id {session.user_id}, "
f"message_count={len(session.messages)}"
)
session = await upsert_chat_session(session)
assert session, "Session not found"
# Generate title for new sessions on first user message (non-blocking)
@@ -492,13 +454,7 @@ async def stream_chat_completion(
asyncio.create_task(_update_title())
# Build system prompt with business understanding
prompt_start = time.monotonic()
system_prompt, understanding = await _build_system_prompt(user_id)
prompt_time = (time.monotonic() - prompt_start) * 1000
logger.info(
f"[TIMING] _build_system_prompt took {prompt_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": prompt_time}},
)
# Initialize variables for streaming
assistant_response = ChatMessage(
@@ -523,27 +479,13 @@ async def stream_chat_completion(
# Generate unique IDs for AI SDK protocol
import uuid as uuid_module
is_continuation = _continuation_message_id is not None
message_id = _continuation_message_id or str(uuid_module.uuid4())
message_id = str(uuid_module.uuid4())
text_block_id = str(uuid_module.uuid4())
# Only yield message start for the initial call, not for continuations.
setup_time = (time.monotonic() - completion_start) * 1000
logger.info(
f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms",
extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
)
if not is_continuation:
yield StreamStart(messageId=message_id, taskId=_task_id)
# Emit start-step before each LLM call (AI SDK uses this to add step boundaries)
yield StreamStartStep()
# Yield message start
yield StreamStart(messageId=message_id)
try:
logger.info(
"[TIMING] Calling _stream_chat_chunks",
extra={"json_fields": log_meta},
)
async for chunk in _stream_chat_chunks(
session=session,
tools=tools,
@@ -643,10 +585,6 @@ async def stream_chat_completion(
)
yield chunk
elif isinstance(chunk, StreamFinish):
if has_done_tool_call:
# Tool calls happened — close the step but don't send message-level finish.
# The continuation will open a new step, and finish will come at the end.
yield StreamFinishStep()
if not has_done_tool_call:
# Emit text-end before finish if we received text but haven't closed it
if has_received_text and not text_streaming_ended:
@@ -678,8 +616,6 @@ async def stream_chat_completion(
has_saved_assistant_message = True
has_yielded_end = True
# Emit finish-step before finish (resets AI SDK text/reasoning state)
yield StreamFinishStep()
yield chunk
elif isinstance(chunk, StreamError):
has_yielded_error = True
@@ -729,10 +665,6 @@ async def stream_chat_completion(
logger.info(
f"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}"
)
# Close the current step before retrying so the recursive call's
# StreamStartStep doesn't produce unbalanced step events.
if not has_yielded_end:
yield StreamFinishStep()
should_retry = True
else:
# Non-retryable error or max retries exceeded
@@ -768,7 +700,6 @@ async def stream_chat_completion(
error_response = StreamError(errorText=error_message)
yield error_response
if not has_yielded_end:
yield StreamFinishStep()
yield StreamFinish()
return
@@ -783,8 +714,6 @@ async def stream_chat_completion(
retry_count=retry_count + 1,
session=session,
context=context,
_continuation_message_id=message_id, # Reuse message ID since start was already sent
_task_id=_task_id,
):
yield chunk
return # Exit after retry to avoid double-saving in finally block
@@ -800,13 +729,9 @@ async def stream_chat_completion(
# Build the messages list in the correct order
messages_to_save: list[ChatMessage] = []
# Add assistant message with tool_calls if any.
# Use extend (not assign) to preserve tool_calls already added by
# _yield_tool_call for long-running tools.
# Add assistant message with tool_calls if any
if accumulated_tool_calls:
if not assistant_response.tool_calls:
assistant_response.tool_calls = []
assistant_response.tool_calls.extend(accumulated_tool_calls)
assistant_response.tool_calls = accumulated_tool_calls
logger.info(
f"Added {len(accumulated_tool_calls)} tool calls to assistant message"
)
@@ -858,8 +783,6 @@ async def stream_chat_completion(
session=session, # Pass session object to avoid Redis refetch
context=context,
tool_call_response=str(tool_response_messages),
_continuation_message_id=message_id, # Reuse message ID to avoid duplicates
_task_id=_task_id,
):
yield chunk
@@ -970,21 +893,9 @@ async def _stream_chat_chunks(
SSE formatted JSON response objects
"""
import time as time_module
stream_chunks_start = time_module.perf_counter()
model = config.model
# Build log metadata for structured logging
log_meta = {"component": "ChatService", "session_id": session.session_id}
if session.user_id:
log_meta["user_id"] = session.user_id
logger.info(
f"[TIMING] _stream_chat_chunks STARTED, session={session.session_id}, "
f"user={session.user_id}, n_messages={len(session.messages)}",
extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
)
logger.info("Starting pure chat stream")
messages = session.to_openai_messages()
if system_prompt:
@@ -995,18 +906,12 @@ async def _stream_chat_chunks(
messages = [system_message] + messages
# Apply context window management
context_start = time_module.perf_counter()
context_result = await _manage_context_window(
messages=messages,
model=model,
api_key=config.api_key,
base_url=config.base_url,
)
context_time = (time_module.perf_counter() - context_start) * 1000
logger.info(
f"[TIMING] _manage_context_window took {context_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": context_time}},
)
if context_result.error:
if "System prompt dropped" in context_result.error:
@@ -1041,19 +946,9 @@ async def _stream_chat_chunks(
while retry_count <= MAX_RETRIES:
try:
elapsed = (time_module.perf_counter() - stream_chunks_start) * 1000
retry_info = (
f" (retry {retry_count}/{MAX_RETRIES})" if retry_count > 0 else ""
)
logger.info(
f"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"retry_count": retry_count,
}
},
f"Creating OpenAI chat completion stream..."
f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}"
)
# Build extra_body for OpenRouter tracing and PostHog analytics
@@ -1070,11 +965,6 @@ async def _stream_chat_chunks(
:128
] # OpenRouter limit
# Enable adaptive thinking for Anthropic models via OpenRouter
if config.thinking_enabled and "anthropic" in model.lower():
extra_body["reasoning"] = {"enabled": True}
api_call_start = time_module.perf_counter()
stream = await client.chat.completions.create(
model=model,
messages=cast(list[ChatCompletionMessageParam], messages),
@@ -1084,11 +974,6 @@ async def _stream_chat_chunks(
stream_options=ChatCompletionStreamOptionsParam(include_usage=True),
extra_body=extra_body,
)
api_init_time = (time_module.perf_counter() - api_call_start) * 1000
logger.info(
f"[TIMING] OpenAI stream object returned in {api_init_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": api_init_time}},
)
# Variables to accumulate tool calls
tool_calls: list[dict[str, Any]] = []
@@ -1099,13 +984,10 @@ async def _stream_chat_chunks(
# Track if we've started the text block
text_started = False
first_content_chunk = True
chunk_count = 0
# Process the stream
chunk: ChatCompletionChunk
async for chunk in stream:
chunk_count += 1
if chunk.usage:
yield StreamUsage(
promptTokens=chunk.usage.prompt_tokens,
@@ -1128,23 +1010,6 @@ async def _stream_chat_chunks(
if not text_started and text_block_id:
yield StreamTextStart(id=text_block_id)
text_started = True
# Log timing for first content chunk
if first_content_chunk:
first_content_chunk = False
ttfc = (
time_module.perf_counter() - api_call_start
) * 1000
logger.info(
f"[TIMING] FIRST CONTENT CHUNK at {ttfc:.1f}ms "
f"(since API call), n_chunks={chunk_count}",
extra={
"json_fields": {
**log_meta,
"time_to_first_chunk_ms": ttfc,
"n_chunks": chunk_count,
}
},
)
# Stream the text delta
text_response = StreamTextDelta(
id=text_block_id or "",
@@ -1201,21 +1066,7 @@ async def _stream_chat_chunks(
toolName=tool_calls[idx]["function"]["name"],
)
emitted_start_for_idx.add(idx)
stream_duration = time_module.perf_counter() - api_call_start
logger.info(
f"[TIMING] OpenAI stream COMPLETE, finish_reason={finish_reason}, "
f"duration={stream_duration:.2f}s, "
f"n_chunks={chunk_count}, n_tool_calls={len(tool_calls)}",
extra={
"json_fields": {
**log_meta,
"stream_duration_ms": stream_duration * 1000,
"finish_reason": finish_reason,
"n_chunks": chunk_count,
"n_tool_calls": len(tool_calls),
}
},
)
logger.info(f"Stream complete. Finish reason: {finish_reason}")
# Yield all accumulated tool calls after the stream is complete
# This ensures all tool call arguments have been fully received
@@ -1235,12 +1086,6 @@ async def _stream_chat_chunks(
# Re-raise to trigger retry logic in the parent function
raise
total_time = (time_module.perf_counter() - stream_chunks_start) * 1000
logger.info(
f"[TIMING] _stream_chat_chunks COMPLETED in {total_time/1000:.1f}s; "
f"session={session.session_id}, user={session.user_id}",
extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
)
yield StreamFinish()
return
except Exception as e:
@@ -1408,9 +1253,13 @@ async def _yield_tool_call(
operation_id=operation_id,
)
# Attach the tool_call to the current turn's assistant message
# (or create one if this is a tool-only response with no text).
session.add_tool_call_to_current_turn(tool_calls[yield_idx])
# Save assistant message with tool_call FIRST (required by LLM)
assistant_message = ChatMessage(
role="assistant",
content="",
tool_calls=[tool_calls[yield_idx]],
)
session.messages.append(assistant_message)
# Then save pending tool result
pending_message = ChatMessage(
@@ -1716,7 +1565,6 @@ async def _execute_long_running_tool_with_streaming(
task_id,
StreamError(errorText=str(e)),
)
await stream_registry.publish_chunk(task_id, StreamFinishStep())
await stream_registry.publish_chunk(task_id, StreamFinish())
await _update_pending_operation(
@@ -1833,10 +1681,6 @@ async def _generate_llm_continuation(
if session_id:
extra_body["session_id"] = session_id[:128]
# Enable adaptive thinking for Anthropic models via OpenRouter
if config.thinking_enabled and "anthropic" in config.model.lower():
extra_body["reasoning"] = {"enabled": True}
retry_count = 0
last_error: Exception | None = None
response = None
@@ -1967,10 +1811,6 @@ async def _generate_llm_continuation_with_streaming(
if session_id:
extra_body["session_id"] = session_id[:128]
# Enable adaptive thinking for Anthropic models via OpenRouter
if config.thinking_enabled and "anthropic" in config.model.lower():
extra_body["reasoning"] = {"enabled": True}
# Make streaming LLM call (no tools - just text response)
from typing import cast
@@ -1982,7 +1822,6 @@ async def _generate_llm_continuation_with_streaming(
# Publish start event
await stream_registry.publish_chunk(task_id, StreamStart(messageId=message_id))
await stream_registry.publish_chunk(task_id, StreamStartStep())
await stream_registry.publish_chunk(task_id, StreamTextStart(id=text_block_id))
# Stream the response
@@ -2006,7 +1845,6 @@ async def _generate_llm_continuation_with_streaming(
# Publish end events
await stream_registry.publish_chunk(task_id, StreamTextEnd(id=text_block_id))
await stream_registry.publish_chunk(task_id, StreamFinishStep())
if assistant_content:
# Reload session from DB to avoid race condition with user messages
@@ -2048,5 +1886,4 @@ async def _generate_llm_continuation_with_streaming(
task_id,
StreamError(errorText=f"Failed to generate response: {e}"),
)
await stream_registry.publish_chunk(task_id, StreamFinishStep())
await stream_registry.publish_chunk(task_id, StreamFinish())

View File

@@ -104,24 +104,6 @@ async def create_task(
Returns:
The created ActiveTask instance (metadata only)
"""
import time
start_time = time.perf_counter()
# Build log metadata for structured logging
log_meta = {
"component": "StreamRegistry",
"task_id": task_id,
"session_id": session_id,
}
if user_id:
log_meta["user_id"] = user_id
logger.info(
f"[TIMING] create_task STARTED, task={task_id}, session={session_id}, user={user_id}",
extra={"json_fields": log_meta},
)
task = ActiveTask(
task_id=task_id,
session_id=session_id,
@@ -132,18 +114,10 @@ async def create_task(
)
# Store metadata in Redis
redis_start = time.perf_counter()
redis = await get_redis_async()
redis_time = (time.perf_counter() - redis_start) * 1000
logger.info(
f"[TIMING] get_redis_async took {redis_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": redis_time}},
)
meta_key = _get_task_meta_key(task_id)
op_key = _get_operation_mapping_key(operation_id)
hset_start = time.perf_counter()
await redis.hset( # type: ignore[misc]
meta_key,
mapping={
@@ -157,22 +131,12 @@ async def create_task(
"created_at": task.created_at.isoformat(),
},
)
hset_time = (time.perf_counter() - hset_start) * 1000
logger.info(
f"[TIMING] redis.hset took {hset_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": hset_time}},
)
await redis.expire(meta_key, config.stream_ttl)
# Create operation_id -> task_id mapping for webhook lookups
await redis.set(op_key, task_id, ex=config.stream_ttl)
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] create_task COMPLETED in {total_time:.1f}ms; task={task_id}, session={session_id}",
extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
)
logger.debug(f"Created task {task_id} for session {session_id}")
return task
@@ -192,60 +156,26 @@ async def publish_chunk(
Returns:
The Redis Stream message ID
"""
import time
start_time = time.perf_counter()
chunk_type = type(chunk).__name__
chunk_json = chunk.model_dump_json()
message_id = "0-0"
# Build log metadata
log_meta = {
"component": "StreamRegistry",
"task_id": task_id,
"chunk_type": chunk_type,
}
try:
redis = await get_redis_async()
stream_key = _get_task_stream_key(task_id)
# Write to Redis Stream for persistence and real-time delivery
xadd_start = time.perf_counter()
raw_id = await redis.xadd(
stream_key,
{"data": chunk_json},
maxlen=config.stream_max_length,
)
xadd_time = (time.perf_counter() - xadd_start) * 1000
message_id = raw_id if isinstance(raw_id, str) else raw_id.decode()
# Set TTL on stream to match task metadata TTL
await redis.expire(stream_key, config.stream_ttl)
total_time = (time.perf_counter() - start_time) * 1000
# Only log timing for significant chunks or slow operations
if (
chunk_type
in ("StreamStart", "StreamFinish", "StreamTextStart", "StreamTextEnd")
or total_time > 50
):
logger.info(
f"[TIMING] publish_chunk {chunk_type} in {total_time:.1f}ms (xadd={xadd_time:.1f}ms)",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"xadd_time_ms": xadd_time,
"message_id": message_id,
}
},
)
except Exception as e:
elapsed = (time.perf_counter() - start_time) * 1000
logger.error(
f"[TIMING] Failed to publish chunk {chunk_type} after {elapsed:.1f}ms: {e}",
extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
f"Failed to publish chunk for task {task_id}: {e}",
exc_info=True,
)
@@ -270,61 +200,24 @@ async def subscribe_to_task(
An asyncio Queue that will receive stream chunks, or None if task not found
or user doesn't have access
"""
import time
start_time = time.perf_counter()
# Build log metadata
log_meta = {"component": "StreamRegistry", "task_id": task_id}
if user_id:
log_meta["user_id"] = user_id
logger.info(
f"[TIMING] subscribe_to_task STARTED, task={task_id}, user={user_id}, last_msg={last_message_id}",
extra={"json_fields": {**log_meta, "last_message_id": last_message_id}},
)
redis_start = time.perf_counter()
redis = await get_redis_async()
meta_key = _get_task_meta_key(task_id)
meta: dict[Any, Any] = await redis.hgetall(meta_key) # type: ignore[misc]
hgetall_time = (time.perf_counter() - redis_start) * 1000
logger.info(
f"[TIMING] Redis hgetall took {hgetall_time:.1f}ms",
extra={"json_fields": {**log_meta, "duration_ms": hgetall_time}},
)
if not meta:
elapsed = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] Task not found in Redis after {elapsed:.1f}ms",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"reason": "task_not_found",
}
},
)
logger.debug(f"Task {task_id} not found in Redis")
return None
# Note: Redis client uses decode_responses=True, so keys are strings
task_status = meta.get("status", "")
task_user_id = meta.get("user_id", "") or None
log_meta["session_id"] = meta.get("session_id", "")
# Validate ownership - if task has an owner, requester must match
if task_user_id:
if user_id != task_user_id:
logger.warning(
f"[TIMING] Access denied: user {user_id} tried to access task owned by {task_user_id}",
extra={
"json_fields": {
**log_meta,
"task_owner": task_user_id,
"reason": "access_denied",
}
},
f"User {user_id} denied access to task {task_id} "
f"owned by {task_user_id}"
)
return None
@@ -332,19 +225,7 @@ async def subscribe_to_task(
stream_key = _get_task_stream_key(task_id)
# Step 1: Replay messages from Redis Stream
xread_start = time.perf_counter()
messages = await redis.xread({stream_key: last_message_id}, block=0, count=1000)
xread_time = (time.perf_counter() - xread_start) * 1000
logger.info(
f"[TIMING] Redis xread (replay) took {xread_time:.1f}ms, status={task_status}",
extra={
"json_fields": {
**log_meta,
"duration_ms": xread_time,
"task_status": task_status,
}
},
)
replayed_count = 0
replay_last_id = last_message_id
@@ -363,48 +244,19 @@ async def subscribe_to_task(
except Exception as e:
logger.warning(f"Failed to replay message: {e}")
logger.info(
f"[TIMING] Replayed {replayed_count} messages, last_id={replay_last_id}",
extra={
"json_fields": {
**log_meta,
"n_messages_replayed": replayed_count,
"replay_last_id": replay_last_id,
}
},
)
logger.debug(f"Task {task_id}: replayed {replayed_count} messages")
# Step 2: If task is still running, start stream listener for live updates
if task_status == "running":
logger.info(
"[TIMING] Task still running, starting _stream_listener",
extra={"json_fields": {**log_meta, "task_status": task_status}},
)
listener_task = asyncio.create_task(
_stream_listener(task_id, subscriber_queue, replay_last_id, log_meta)
_stream_listener(task_id, subscriber_queue, replay_last_id)
)
# Track listener task for cleanup on unsubscribe
_listener_tasks[id(subscriber_queue)] = (task_id, listener_task)
else:
# Task is completed/failed - add finish marker
logger.info(
f"[TIMING] Task already {task_status}, adding StreamFinish",
extra={"json_fields": {**log_meta, "task_status": task_status}},
)
await subscriber_queue.put(StreamFinish())
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] subscribe_to_task COMPLETED in {total_time:.1f}ms; task={task_id}, "
f"n_messages_replayed={replayed_count}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"n_messages_replayed": replayed_count,
}
},
)
return subscriber_queue
@@ -412,7 +264,6 @@ async def _stream_listener(
task_id: str,
subscriber_queue: asyncio.Queue[StreamBaseResponse],
last_replayed_id: str,
log_meta: dict | None = None,
) -> None:
"""Listen to Redis Stream for new messages using blocking XREAD.
@@ -423,27 +274,10 @@ async def _stream_listener(
task_id: Task ID to listen for
subscriber_queue: Queue to deliver messages to
last_replayed_id: Last message ID from replay (continue from here)
log_meta: Structured logging metadata
"""
import time
start_time = time.perf_counter()
# Use provided log_meta or build minimal one
if log_meta is None:
log_meta = {"component": "StreamRegistry", "task_id": task_id}
logger.info(
f"[TIMING] _stream_listener STARTED, task={task_id}, last_id={last_replayed_id}",
extra={"json_fields": {**log_meta, "last_replayed_id": last_replayed_id}},
)
queue_id = id(subscriber_queue)
# Track the last successfully delivered message ID for recovery hints
last_delivered_id = last_replayed_id
messages_delivered = 0
first_message_time = None
xread_count = 0
try:
redis = await get_redis_async()
@@ -453,39 +287,9 @@ async def _stream_listener(
while True:
# Block for up to 30 seconds waiting for new messages
# This allows periodic checking if task is still running
xread_start = time.perf_counter()
xread_count += 1
messages = await redis.xread(
{stream_key: current_id}, block=30000, count=100
)
xread_time = (time.perf_counter() - xread_start) * 1000
if messages:
msg_count = sum(len(msgs) for _, msgs in messages)
logger.info(
f"[TIMING] xread #{xread_count} returned {msg_count} messages in {xread_time:.1f}ms",
extra={
"json_fields": {
**log_meta,
"xread_count": xread_count,
"n_messages": msg_count,
"duration_ms": xread_time,
}
},
)
elif xread_time > 1000:
# Only log timeouts (30s blocking)
logger.info(
f"[TIMING] xread #{xread_count} timeout after {xread_time:.1f}ms",
extra={
"json_fields": {
**log_meta,
"xread_count": xread_count,
"duration_ms": xread_time,
"reason": "timeout",
}
},
)
if not messages:
# Timeout - check if task is still running
@@ -522,30 +326,10 @@ async def _stream_listener(
)
# Update last delivered ID on successful delivery
last_delivered_id = current_id
messages_delivered += 1
if first_message_time is None:
first_message_time = time.perf_counter()
elapsed = (first_message_time - start_time) * 1000
logger.info(
f"[TIMING] FIRST live message at {elapsed:.1f}ms, type={type(chunk).__name__}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"chunk_type": type(chunk).__name__,
}
},
)
except asyncio.TimeoutError:
logger.warning(
f"[TIMING] Subscriber queue full, delivery timed out after {QUEUE_PUT_TIMEOUT}s",
extra={
"json_fields": {
**log_meta,
"timeout_s": QUEUE_PUT_TIMEOUT,
"reason": "queue_full",
}
},
f"Subscriber queue full for task {task_id}, "
f"message delivery timed out after {QUEUE_PUT_TIMEOUT}s"
)
# Send overflow error with recovery info
try:
@@ -567,44 +351,15 @@ async def _stream_listener(
# Stop listening on finish
if isinstance(chunk, StreamFinish):
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] StreamFinish received in {total_time/1000:.1f}s; delivered={messages_delivered}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"messages_delivered": messages_delivered,
}
},
)
return
except Exception as e:
logger.warning(
f"Error processing stream message: {e}",
extra={"json_fields": {**log_meta, "error": str(e)}},
)
logger.warning(f"Error processing stream message: {e}")
except asyncio.CancelledError:
elapsed = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] _stream_listener CANCELLED after {elapsed:.1f}ms, delivered={messages_delivered}",
extra={
"json_fields": {
**log_meta,
"elapsed_ms": elapsed,
"messages_delivered": messages_delivered,
"reason": "cancelled",
}
},
)
logger.debug(f"Stream listener cancelled for task {task_id}")
raise # Re-raise to propagate cancellation
except Exception as e:
elapsed = (time.perf_counter() - start_time) * 1000
logger.error(
f"[TIMING] _stream_listener ERROR after {elapsed:.1f}ms: {e}",
extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
)
logger.error(f"Stream listener error for task {task_id}: {e}")
# On error, send finish to unblock subscriber
try:
await asyncio.wait_for(
@@ -613,24 +368,10 @@ async def _stream_listener(
)
except (asyncio.TimeoutError, asyncio.QueueFull):
logger.warning(
"Could not deliver finish event after error",
extra={"json_fields": log_meta},
f"Could not deliver finish event for task {task_id} after error"
)
finally:
# Clean up listener task mapping on exit
total_time = (time.perf_counter() - start_time) * 1000
logger.info(
f"[TIMING] _stream_listener FINISHED in {total_time/1000:.1f}s; task={task_id}, "
f"delivered={messages_delivered}, xread_count={xread_count}",
extra={
"json_fields": {
**log_meta,
"total_time_ms": total_time,
"messages_delivered": messages_delivered,
"xread_count": xread_count,
}
},
)
_listener_tasks.pop(queue_id, None)
@@ -857,10 +598,8 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
ResponseType,
StreamError,
StreamFinish,
StreamFinishStep,
StreamHeartbeat,
StreamStart,
StreamStartStep,
StreamTextDelta,
StreamTextEnd,
StreamTextStart,
@@ -874,8 +613,6 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
type_to_class: dict[str, type[StreamBaseResponse]] = {
ResponseType.START.value: StreamStart,
ResponseType.FINISH.value: StreamFinish,
ResponseType.START_STEP.value: StreamStartStep,
ResponseType.FINISH_STEP.value: StreamFinishStep,
ResponseType.TEXT_START.value: StreamTextStart,
ResponseType.TEXT_DELTA.value: StreamTextDelta,
ResponseType.TEXT_END.value: StreamTextEnd,

View File

@@ -1,154 +0,0 @@
"""Dummy Agent Generator for testing.
Returns mock responses matching the format expected from the external service.
Enable via AGENTGENERATOR_USE_DUMMY=true in settings.
WARNING: This is for testing only. Do not use in production.
"""
import asyncio
import logging
import uuid
from typing import Any
logger = logging.getLogger(__name__)
# Dummy decomposition result (instructions type)
DUMMY_DECOMPOSITION_RESULT: dict[str, Any] = {
"type": "instructions",
"steps": [
{
"description": "Get input from user",
"action": "input",
"block_name": "AgentInputBlock",
},
{
"description": "Process the input",
"action": "process",
"block_name": "TextFormatterBlock",
},
{
"description": "Return output to user",
"action": "output",
"block_name": "AgentOutputBlock",
},
],
}
# Block IDs from backend/blocks/io.py
AGENT_INPUT_BLOCK_ID = "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b"
AGENT_OUTPUT_BLOCK_ID = "363ae599-353e-4804-937e-b2ee3cef3da4"
def _generate_dummy_agent_json() -> dict[str, Any]:
"""Generate a minimal valid agent JSON for testing."""
input_node_id = str(uuid.uuid4())
output_node_id = str(uuid.uuid4())
return {
"id": str(uuid.uuid4()),
"version": 1,
"is_active": True,
"name": "Dummy Test Agent",
"description": "A dummy agent generated for testing purposes",
"nodes": [
{
"id": input_node_id,
"block_id": AGENT_INPUT_BLOCK_ID,
"input_default": {
"name": "input",
"title": "Input",
"description": "Enter your input",
"placeholder_values": [],
},
"metadata": {"position": {"x": 0, "y": 0}},
},
{
"id": output_node_id,
"block_id": AGENT_OUTPUT_BLOCK_ID,
"input_default": {
"name": "output",
"title": "Output",
"description": "Agent output",
"format": "{output}",
},
"metadata": {"position": {"x": 400, "y": 0}},
},
],
"links": [
{
"id": str(uuid.uuid4()),
"source_id": input_node_id,
"sink_id": output_node_id,
"source_name": "result",
"sink_name": "value",
"is_static": False,
},
],
}
async def decompose_goal_dummy(
description: str,
context: str = "",
library_agents: list[dict[str, Any]] | None = None,
) -> dict[str, Any]:
"""Return dummy decomposition result."""
logger.info("Using dummy agent generator for decompose_goal")
return DUMMY_DECOMPOSITION_RESULT.copy()
async def generate_agent_dummy(
instructions: dict[str, Any],
library_agents: list[dict[str, Any]] | None = None,
operation_id: str | None = None,
task_id: str | None = None,
) -> dict[str, Any]:
"""Return dummy agent JSON after a simulated delay."""
logger.info("Using dummy agent generator for generate_agent (30s delay)")
await asyncio.sleep(30)
return _generate_dummy_agent_json()
async def generate_agent_patch_dummy(
update_request: str,
current_agent: dict[str, Any],
library_agents: list[dict[str, Any]] | None = None,
operation_id: str | None = None,
task_id: str | None = None,
) -> dict[str, Any]:
"""Return dummy patched agent (returns the current agent with updated description)."""
logger.info("Using dummy agent generator for generate_agent_patch")
patched = current_agent.copy()
patched["description"] = (
f"{current_agent.get('description', '')} (updated: {update_request})"
)
return patched
async def customize_template_dummy(
template_agent: dict[str, Any],
modification_request: str,
context: str = "",
) -> dict[str, Any]:
"""Return dummy customized template (returns template with updated description)."""
logger.info("Using dummy agent generator for customize_template")
customized = template_agent.copy()
customized["description"] = (
f"{template_agent.get('description', '')} (customized: {modification_request})"
)
return customized
async def get_blocks_dummy() -> list[dict[str, Any]]:
"""Return dummy blocks list."""
logger.info("Using dummy agent generator for get_blocks")
return [
{"id": AGENT_INPUT_BLOCK_ID, "name": "AgentInputBlock"},
{"id": AGENT_OUTPUT_BLOCK_ID, "name": "AgentOutputBlock"},
]
async def health_check_dummy() -> bool:
"""Always returns healthy for dummy service."""
return True

View File

@@ -12,19 +12,8 @@ import httpx
from backend.util.settings import Settings
from .dummy import (
customize_template_dummy,
decompose_goal_dummy,
generate_agent_dummy,
generate_agent_patch_dummy,
get_blocks_dummy,
health_check_dummy,
)
logger = logging.getLogger(__name__)
_dummy_mode_warned = False
def _create_error_response(
error_message: str,
@@ -101,26 +90,10 @@ def _get_settings() -> Settings:
return _settings
def _is_dummy_mode() -> bool:
"""Check if dummy mode is enabled for testing."""
global _dummy_mode_warned
settings = _get_settings()
is_dummy = bool(settings.config.agentgenerator_use_dummy)
if is_dummy and not _dummy_mode_warned:
logger.warning(
"Agent Generator running in DUMMY MODE - returning mock responses. "
"Do not use in production!"
)
_dummy_mode_warned = True
return is_dummy
def is_external_service_configured() -> bool:
"""Check if external Agent Generator service is configured (or dummy mode)."""
"""Check if external Agent Generator service is configured."""
settings = _get_settings()
return bool(settings.config.agentgenerator_host) or bool(
settings.config.agentgenerator_use_dummy
)
return bool(settings.config.agentgenerator_host)
def _get_base_url() -> str:
@@ -164,9 +137,6 @@ async def decompose_goal_external(
- {"type": "error", "error": "...", "error_type": "..."} on error
Or None on unexpected error
"""
if _is_dummy_mode():
return await decompose_goal_dummy(description, context, library_agents)
client = _get_client()
if context:
@@ -256,11 +226,6 @@ async def generate_agent_external(
Returns:
Agent JSON dict, {"status": "accepted"} for async, or error dict {"type": "error", ...} on error
"""
if _is_dummy_mode():
return await generate_agent_dummy(
instructions, library_agents, operation_id, task_id
)
client = _get_client()
# Build request payload
@@ -332,11 +297,6 @@ async def generate_agent_patch_external(
Returns:
Updated agent JSON, clarifying questions dict, {"status": "accepted"} for async, or error dict on error
"""
if _is_dummy_mode():
return await generate_agent_patch_dummy(
update_request, current_agent, library_agents, operation_id, task_id
)
client = _get_client()
# Build request payload
@@ -423,11 +383,6 @@ async def customize_template_external(
Returns:
Customized agent JSON, clarifying questions dict, or error dict on error
"""
if _is_dummy_mode():
return await customize_template_dummy(
template_agent, modification_request, context
)
client = _get_client()
request = modification_request
@@ -490,9 +445,6 @@ async def get_blocks_external() -> list[dict[str, Any]] | None:
Returns:
List of block info dicts or None on error
"""
if _is_dummy_mode():
return await get_blocks_dummy()
client = _get_client()
try:
@@ -526,9 +478,6 @@ async def health_check() -> bool:
if not is_external_service_configured():
return False
if _is_dummy_mode():
return await health_check_dummy()
client = _get_client()
try:

View File

@@ -13,8 +13,7 @@ from backend.api.features.chat.tools.models import (
NoResultsResponse,
)
from backend.api.features.store.hybrid_search import unified_hybrid_search
from backend.blocks import get_block
from backend.blocks._base import BlockType
from backend.data.block import BlockType, get_block
logger = logging.getLogger(__name__)

View File

@@ -10,7 +10,7 @@ from backend.api.features.chat.tools.find_block import (
FindBlockTool,
)
from backend.api.features.chat.tools.models import BlockListResponse
from backend.blocks._base import BlockType
from backend.data.block import BlockType
from ._test_data import make_session

View File

@@ -1,29 +0,0 @@
"""Shared helpers for chat tools."""
from typing import Any
def get_inputs_from_schema(
input_schema: dict[str, Any],
exclude_fields: set[str] | None = None,
) -> list[dict[str, Any]]:
"""Extract input field info from JSON schema."""
if not isinstance(input_schema, dict):
return []
exclude = exclude_fields or set()
properties = input_schema.get("properties", {})
required = set(input_schema.get("required", []))
return [
{
"name": name,
"title": schema.get("title", name),
"type": schema.get("type", "string"),
"description": schema.get("description", ""),
"required": name in required,
"default": schema.get("default"),
}
for name, schema in properties.items()
if name not in exclude
]

View File

@@ -24,7 +24,6 @@ from backend.util.timezone_utils import (
)
from .base import BaseTool
from .helpers import get_inputs_from_schema
from .models import (
AgentDetails,
AgentDetailsResponse,
@@ -262,7 +261,7 @@ class RunAgentTool(BaseTool):
),
requirements={
"credentials": requirements_creds_list,
"inputs": get_inputs_from_schema(graph.input_schema),
"inputs": self._get_inputs_list(graph.input_schema),
"execution_modes": self._get_execution_modes(graph),
},
),
@@ -370,6 +369,22 @@ class RunAgentTool(BaseTool):
session_id=session_id,
)
def _get_inputs_list(self, input_schema: dict[str, Any]) -> list[dict[str, Any]]:
"""Extract inputs list from schema."""
inputs_list = []
if isinstance(input_schema, dict) and "properties" in input_schema:
for field_name, field_schema in input_schema["properties"].items():
inputs_list.append(
{
"name": field_name,
"title": field_schema.get("title", field_name),
"type": field_schema.get("type", "string"),
"description": field_schema.get("description", ""),
"required": field_name in input_schema.get("required", []),
}
)
return inputs_list
def _get_execution_modes(self, graph: GraphModel) -> list[str]:
"""Get available execution modes for the graph."""
trigger_info = graph.trigger_setup_info
@@ -383,7 +398,7 @@ class RunAgentTool(BaseTool):
suffix: str,
) -> str:
"""Build a message describing available inputs for an agent."""
inputs_list = get_inputs_from_schema(graph.input_schema)
inputs_list = self._get_inputs_list(graph.input_schema)
required_names = [i["name"] for i in inputs_list if i["required"]]
optional_names = [i["name"] for i in inputs_list if not i["required"]]

View File

@@ -12,16 +12,14 @@ from backend.api.features.chat.tools.find_block import (
COPILOT_EXCLUDED_BLOCK_IDS,
COPILOT_EXCLUDED_BLOCK_TYPES,
)
from backend.blocks import get_block
from backend.blocks._base import AnyBlockSchema
from backend.data.block import get_block
from backend.data.execution import ExecutionContext
from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
from backend.data.model import CredentialsMetaInput
from backend.data.workspace import get_or_create_workspace
from backend.integrations.creds_manager import IntegrationCredentialsManager
from backend.util.exceptions import BlockError
from .base import BaseTool
from .helpers import get_inputs_from_schema
from .models import (
BlockOutputResponse,
ErrorResponse,
@@ -30,10 +28,7 @@ from .models import (
ToolResponseBase,
UserReadiness,
)
from .utils import (
build_missing_credentials_from_field_info,
match_credentials_to_requirements,
)
from .utils import build_missing_credentials_from_field_info
logger = logging.getLogger(__name__)
@@ -82,6 +77,91 @@ class RunBlockTool(BaseTool):
def requires_auth(self) -> bool:
return True
async def _check_block_credentials(
self,
user_id: str,
block: Any,
input_data: dict[str, Any] | None = None,
) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
"""
Check if user has required credentials for a block.
Args:
user_id: User ID
block: Block to check credentials for
input_data: Input data for the block (used to determine provider via discriminator)
Returns:
tuple[matched_credentials, missing_credentials]
"""
matched_credentials: dict[str, CredentialsMetaInput] = {}
missing_credentials: list[CredentialsMetaInput] = []
input_data = input_data or {}
# Get credential field info from block's input schema
credentials_fields_info = block.input_schema.get_credentials_fields_info()
if not credentials_fields_info:
return matched_credentials, missing_credentials
# Get user's available credentials
creds_manager = IntegrationCredentialsManager()
available_creds = await creds_manager.store.get_all_creds(user_id)
for field_name, field_info in credentials_fields_info.items():
effective_field_info = field_info
if field_info.discriminator and field_info.discriminator_mapping:
# Get discriminator from input, falling back to schema default
discriminator_value = input_data.get(field_info.discriminator)
if discriminator_value is None:
field = block.input_schema.model_fields.get(
field_info.discriminator
)
if field and field.default is not PydanticUndefined:
discriminator_value = field.default
if (
discriminator_value
and discriminator_value in field_info.discriminator_mapping
):
effective_field_info = field_info.discriminate(discriminator_value)
logger.debug(
f"Discriminated provider for {field_name}: "
f"{discriminator_value} -> {effective_field_info.provider}"
)
matching_cred = next(
(
cred
for cred in available_creds
if cred.provider in effective_field_info.provider
and cred.type in effective_field_info.supported_types
),
None,
)
if matching_cred:
matched_credentials[field_name] = CredentialsMetaInput(
id=matching_cred.id,
provider=matching_cred.provider, # type: ignore
type=matching_cred.type,
title=matching_cred.title,
)
else:
# Create a placeholder for the missing credential
provider = next(iter(effective_field_info.provider), "unknown")
cred_type = next(iter(effective_field_info.supported_types), "api_key")
missing_credentials.append(
CredentialsMetaInput(
id=field_name,
provider=provider, # type: ignore
type=cred_type, # type: ignore
title=field_name.replace("_", " ").title(),
)
)
return matched_credentials, missing_credentials
async def _execute(
self,
user_id: str | None,
@@ -152,8 +232,8 @@ class RunBlockTool(BaseTool):
logger.info(f"Executing block {block.name} ({block_id}) for user {user_id}")
creds_manager = IntegrationCredentialsManager()
matched_credentials, missing_credentials = (
await self._resolve_block_credentials(user_id, block, input_data)
matched_credentials, missing_credentials = await self._check_block_credentials(
user_id, block, input_data
)
if missing_credentials:
@@ -282,75 +362,29 @@ class RunBlockTool(BaseTool):
session_id=session_id,
)
async def _resolve_block_credentials(
self,
user_id: str,
block: AnyBlockSchema,
input_data: dict[str, Any] | None = None,
) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
"""
Resolve credentials for a block by matching user's available credentials.
Args:
user_id: User ID
block: Block to resolve credentials for
input_data: Input data for the block (used to determine provider via discriminator)
Returns:
tuple of (matched_credentials, missing_credentials) - matched credentials
are used for block execution, missing ones indicate setup requirements.
"""
input_data = input_data or {}
requirements = self._resolve_discriminated_credentials(block, input_data)
if not requirements:
return {}, []
return await match_credentials_to_requirements(user_id, requirements)
def _get_inputs_list(self, block: AnyBlockSchema) -> list[dict[str, Any]]:
def _get_inputs_list(self, block: Any) -> list[dict[str, Any]]:
"""Extract non-credential inputs from block schema."""
inputs_list = []
schema = block.input_schema.jsonschema()
properties = schema.get("properties", {})
required_fields = set(schema.get("required", []))
# Get credential field names to exclude
credentials_fields = set(block.input_schema.get_credentials_fields().keys())
return get_inputs_from_schema(schema, exclude_fields=credentials_fields)
def _resolve_discriminated_credentials(
self,
block: AnyBlockSchema,
input_data: dict[str, Any],
) -> dict[str, CredentialsFieldInfo]:
"""Resolve credential requirements, applying discriminator logic where needed."""
credentials_fields_info = block.input_schema.get_credentials_fields_info()
if not credentials_fields_info:
return {}
for field_name, field_schema in properties.items():
# Skip credential fields
if field_name in credentials_fields:
continue
resolved: dict[str, CredentialsFieldInfo] = {}
inputs_list.append(
{
"name": field_name,
"title": field_schema.get("title", field_name),
"type": field_schema.get("type", "string"),
"description": field_schema.get("description", ""),
"required": field_name in required_fields,
}
)
for field_name, field_info in credentials_fields_info.items():
effective_field_info = field_info
if field_info.discriminator and field_info.discriminator_mapping:
discriminator_value = input_data.get(field_info.discriminator)
if discriminator_value is None:
field = block.input_schema.model_fields.get(
field_info.discriminator
)
if field and field.default is not PydanticUndefined:
discriminator_value = field.default
if (
discriminator_value
and discriminator_value in field_info.discriminator_mapping
):
effective_field_info = field_info.discriminate(discriminator_value)
# For host-scoped credentials, add the discriminator value
# (e.g., URL) so _credential_is_for_host can match it
effective_field_info.discriminator_values.add(discriminator_value)
logger.debug(
f"Discriminated provider for {field_name}: "
f"{discriminator_value} -> {effective_field_info.provider}"
)
resolved[field_name] = effective_field_info
return resolved
return inputs_list

View File

@@ -6,7 +6,7 @@ import pytest
from backend.api.features.chat.tools.models import ErrorResponse
from backend.api.features.chat.tools.run_block import RunBlockTool
from backend.blocks._base import BlockType
from backend.data.block import BlockType
from ._test_data import make_session

View File

@@ -8,7 +8,6 @@ from backend.api.features.library import model as library_model
from backend.api.features.store import db as store_db
from backend.data.graph import GraphModel
from backend.data.model import (
Credentials,
CredentialsFieldInfo,
CredentialsMetaInput,
HostScopedCredentials,
@@ -224,99 +223,6 @@ async def get_or_create_library_agent(
return library_agents[0]
async def match_credentials_to_requirements(
user_id: str,
requirements: dict[str, CredentialsFieldInfo],
) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
"""
Match user's credentials against a dictionary of credential requirements.
This is the core matching logic shared by both graph and block credential matching.
"""
matched: dict[str, CredentialsMetaInput] = {}
missing: list[CredentialsMetaInput] = []
if not requirements:
return matched, missing
available_creds = await get_user_credentials(user_id)
for field_name, field_info in requirements.items():
matching_cred = find_matching_credential(available_creds, field_info)
if matching_cred:
try:
matched[field_name] = create_credential_meta_from_match(matching_cred)
except Exception as e:
logger.error(
f"Failed to create CredentialsMetaInput for field '{field_name}': "
f"provider={matching_cred.provider}, type={matching_cred.type}, "
f"credential_id={matching_cred.id}",
exc_info=True,
)
provider = next(iter(field_info.provider), "unknown")
cred_type = next(iter(field_info.supported_types), "api_key")
missing.append(
CredentialsMetaInput(
id=field_name,
provider=provider, # type: ignore
type=cred_type, # type: ignore
title=f"{field_name} (validation failed: {e})",
)
)
else:
provider = next(iter(field_info.provider), "unknown")
cred_type = next(iter(field_info.supported_types), "api_key")
missing.append(
CredentialsMetaInput(
id=field_name,
provider=provider, # type: ignore
type=cred_type, # type: ignore
title=field_name.replace("_", " ").title(),
)
)
return matched, missing
async def get_user_credentials(user_id: str) -> list[Credentials]:
"""Get all available credentials for a user."""
creds_manager = IntegrationCredentialsManager()
return await creds_manager.store.get_all_creds(user_id)
def find_matching_credential(
available_creds: list[Credentials],
field_info: CredentialsFieldInfo,
) -> Credentials | None:
"""Find a credential that matches the required provider, type, scopes, and host."""
for cred in available_creds:
if cred.provider not in field_info.provider:
continue
if cred.type not in field_info.supported_types:
continue
if cred.type == "oauth2" and not _credential_has_required_scopes(
cred, field_info
):
continue
if cred.type == "host_scoped" and not _credential_is_for_host(cred, field_info):
continue
return cred
return None
def create_credential_meta_from_match(
matching_cred: Credentials,
) -> CredentialsMetaInput:
"""Create a CredentialsMetaInput from a matched credential."""
return CredentialsMetaInput(
id=matching_cred.id,
provider=matching_cred.provider, # type: ignore
type=matching_cred.type,
title=matching_cred.title,
)
async def match_user_credentials_to_graph(
user_id: str,
graph: GraphModel,
@@ -425,6 +331,8 @@ def _credential_has_required_scopes(
# If no scopes are required, any credential matches
if not requirements.required_scopes:
return True
# Check that credential scopes are a superset of required scopes
return set(credential.scopes).issuperset(requirements.required_scopes)

View File

@@ -7,17 +7,17 @@ import prisma.errors
import prisma.models
import prisma.types
from backend.api.features.library.exceptions import FolderValidationError
import backend.api.features.store.exceptions as store_exceptions
import backend.api.features.store.image_gen as store_image_gen
import backend.api.features.store.media as store_media
import backend.data.graph as graph_db
import backend.data.integrations as integrations_db
from backend.data.block import BlockInput
from backend.data.db import transaction
from backend.data.execution import get_graph_execution
from backend.data.graph import GraphSettings
from backend.data.includes import AGENT_PRESET_INCLUDE, library_agent_include
from backend.data.model import CredentialsMetaInput, GraphInput
from backend.data.model import CredentialsMetaInput
from backend.integrations.creds_manager import IntegrationCredentialsManager
from backend.integrations.webhooks.graph_lifecycle_hooks import (
on_graph_activate,
@@ -43,8 +43,6 @@ async def list_library_agents(
page: int = 1,
page_size: int = 50,
include_executions: bool = False,
folder_id: Optional[str] = None,
include_root_only: bool = False,
) -> library_model.LibraryAgentResponse:
"""
Retrieves a paginated list of LibraryAgent records for a given user.
@@ -55,8 +53,6 @@ async def list_library_agents(
sort_by: Sorting field (createdAt, updatedAt, isFavorite, isCreatedByUser).
page: Current page (1-indexed).
page_size: Number of items per page.
folder_id: Filter by folder ID. If provided, only returns agents in this folder.
include_root_only: If True, only returns agents without a folder (root-level).
include_executions: Whether to include execution data for status calculation.
Defaults to False for performance (UI fetches status separately).
Set to True when accurate status/metrics are needed (e.g., agent generator).
@@ -87,13 +83,6 @@ async def list_library_agents(
"isArchived": False,
}
# Apply folder filter
if folder_id is not None:
where_clause["folderId"] = folder_id
elif include_root_only:
where_clause["folderId"] = None
# Build search filter if applicable
if search_term:
where_clause["OR"] = [
{
@@ -646,7 +635,6 @@ async def update_library_agent(
is_archived: Optional[bool] = None,
is_deleted: Optional[Literal[False]] = None,
settings: Optional[GraphSettings] = None,
folder_id: Optional[str] = None,
) -> library_model.LibraryAgent:
"""
Updates the specified LibraryAgent record.
@@ -659,7 +647,6 @@ async def update_library_agent(
is_favorite: Whether this agent is marked as a favorite.
is_archived: Whether this agent is archived.
settings: User-specific settings for this library agent.
folder_id: Folder ID to move agent to (empty string "" for root, None to skip).
Returns:
The updated LibraryAgent.
@@ -687,7 +674,13 @@ async def update_library_agent(
)
update_fields["isDeleted"] = is_deleted
if settings is not None:
update_fields["settings"] = SafeJson(settings.model_dump())
existing_agent = await get_library_agent(id=library_agent_id, user_id=user_id)
current_settings_dict = (
existing_agent.settings.model_dump() if existing_agent.settings else {}
)
new_settings = settings.model_dump(exclude_unset=True)
merged_settings = {**current_settings_dict, **new_settings}
update_fields["settings"] = SafeJson(merged_settings)
try:
# If graph_version is provided, update to that specific version
@@ -926,788 +919,6 @@ async def add_store_agent_to_library(
raise DatabaseError("Failed to add agent to library") from e
##############################################
############ Folder DB Functions #############
##############################################
MAX_FOLDER_DEPTH = 5
async def list_folders(
user_id: str,
parent_id: Optional[str] = None,
include_counts: bool = True,
) -> list[library_model.LibraryFolder]:
"""
Lists folders for a user, optionally filtered by parent.
Args:
user_id: The ID of the user.
parent_id: If provided, only returns folders with this parent.
If None, returns root-level folders.
include_counts: Whether to include agent and subfolder counts.
Returns:
A list of LibraryFolder objects.
"""
logger.debug(f"Listing folders for user #{user_id}, parent_id={parent_id}")
try:
where_clause: prisma.types.LibraryFolderWhereInput = {
"userId": user_id,
"isDeleted": False,
"parentId": parent_id,
}
folders = await prisma.models.LibraryFolder.prisma().find_many(
where=where_clause,
order={"createdAt": "asc"},
include=(
{
"LibraryAgents": {"where": {"isDeleted": False}},
"Children": {"where": {"isDeleted": False}},
}
if include_counts
else None
),
)
result = []
for folder in folders:
agent_count = len(folder.LibraryAgents) if folder.LibraryAgents else 0
subfolder_count = len(folder.Children) if folder.Children else 0
result.append(
library_model.LibraryFolder.from_db(
folder,
agent_count=agent_count,
subfolder_count=subfolder_count,
)
)
return result
except prisma.errors.PrismaError as e:
logger.error(f"Database error listing folders: {e}")
raise DatabaseError("Failed to list folders") from e
async def get_folder_tree(
user_id: str,
) -> list[library_model.LibraryFolderTree]:
"""
Gets the full folder tree for a user.
Args:
user_id: The ID of the user.
Returns:
A list of LibraryFolderTree objects (root folders with nested children).
"""
logger.debug(f"Getting folder tree for user #{user_id}")
try:
# Fetch all folders for the user
all_folders = await prisma.models.LibraryFolder.prisma().find_many(
where={
"userId": user_id,
"isDeleted": False,
},
order={"createdAt": "asc"},
include={
"LibraryAgents": {"where": {"isDeleted": False}},
"Children": {"where": {"isDeleted": False}},
},
)
# Build a map of folder ID to folder data
folder_map: dict[str, library_model.LibraryFolderTree] = {}
for folder in all_folders:
agent_count = len(folder.LibraryAgents) if folder.LibraryAgents else 0
subfolder_count = len(folder.Children) if folder.Children else 0
folder_map[folder.id] = library_model.LibraryFolderTree(
**library_model.LibraryFolder.from_db(
folder,
agent_count=agent_count,
subfolder_count=subfolder_count,
).model_dump(),
children=[],
)
# Build the tree structure
root_folders: list[library_model.LibraryFolderTree] = []
for folder in all_folders:
tree_folder = folder_map[folder.id]
if folder.parentId and folder.parentId in folder_map:
folder_map[folder.parentId].children.append(tree_folder)
else:
root_folders.append(tree_folder)
return root_folders
except prisma.errors.PrismaError as e:
logger.error(f"Database error getting folder tree: {e}")
raise DatabaseError("Failed to get folder tree") from e
async def get_folder(
folder_id: str,
user_id: str,
) -> library_model.LibraryFolder:
"""
Gets a single folder by ID.
Args:
folder_id: The ID of the folder.
user_id: The ID of the user (for ownership verification).
Returns:
The LibraryFolder object.
Raises:
NotFoundError: If the folder doesn't exist or doesn't belong to the user.
"""
try:
folder = await prisma.models.LibraryFolder.prisma().find_first(
where={
"id": folder_id,
"userId": user_id,
"isDeleted": False,
},
include={
"LibraryAgents": {"where": {"isDeleted": False}},
"Children": {"where": {"isDeleted": False}},
},
)
if not folder:
raise NotFoundError(f"Folder #{folder_id} not found")
agent_count = len(folder.LibraryAgents) if folder.LibraryAgents else 0
subfolder_count = len(folder.Children) if folder.Children else 0
return library_model.LibraryFolder.from_db(
folder,
agent_count=agent_count,
subfolder_count=subfolder_count,
)
except prisma.errors.PrismaError as e:
logger.error(f"Database error getting folder: {e}")
raise DatabaseError("Failed to get folder") from e
async def get_folder_depth(folder_id: str, user_id: str) -> int:
"""
Calculate the depth of a folder in the hierarchy (root=0).
Args:
folder_id: The ID of the folder.
user_id: The ID of the user.
Returns:
The depth of the folder (0 for root-level folders).
"""
depth = 0
current_id: str | None = folder_id
while current_id:
folder = await prisma.models.LibraryFolder.prisma().find_first(
where={
"id": current_id,
"userId": user_id,
"isDeleted": False,
}
)
if not folder:
break
if folder.parentId:
depth += 1
current_id = folder.parentId
else:
break
return depth
async def is_descendant_of(
folder_id: str,
potential_ancestor_id: str,
user_id: str,
) -> bool:
"""
Check if folder_id is a descendant of potential_ancestor_id.
Args:
folder_id: The ID of the folder to check.
potential_ancestor_id: The ID of the potential ancestor.
user_id: The ID of the user.
Returns:
True if folder_id is a descendant of potential_ancestor_id.
"""
current_id: str | None = folder_id
while current_id:
if current_id == potential_ancestor_id:
return True
folder = await prisma.models.LibraryFolder.prisma().find_first(
where={
"id": current_id,
"userId": user_id,
"isDeleted": False,
}
)
if not folder or not folder.parentId:
break
current_id = folder.parentId
return False
async def validate_folder_operation(
folder_id: Optional[str],
target_parent_id: Optional[str],
user_id: str,
max_depth: int = MAX_FOLDER_DEPTH,
) -> None:
"""
Validate that a folder move/create operation is valid.
Args:
folder_id: The ID of the folder being moved (None for create).
target_parent_id: The target parent ID (None for root).
user_id: The ID of the user.
max_depth: Maximum allowed nesting depth.
Raises:
FolderValidationError: If the operation is invalid.
"""
# Cannot move folder into itself
if folder_id and folder_id == target_parent_id:
raise FolderValidationError("Cannot move folder into itself")
# Check for circular reference
if folder_id and target_parent_id:
if await is_descendant_of(target_parent_id, folder_id, user_id):
raise FolderValidationError("Cannot move folder into its own descendant")
# Check depth limit
if target_parent_id:
parent_depth = await get_folder_depth(target_parent_id, user_id)
if parent_depth + 1 >= max_depth:
raise FolderValidationError(
f"Maximum folder nesting depth of {max_depth} exceeded"
)
async def create_folder(
user_id: str,
name: str,
parent_id: Optional[str] = None,
icon: Optional[str] = None,
color: Optional[str] = None,
) -> library_model.LibraryFolder:
"""
Creates a new folder for the user.
Args:
user_id: The ID of the user.
name: The folder name.
parent_id: Optional parent folder ID.
icon: Optional icon identifier.
color: Optional hex color code.
Returns:
The created LibraryFolder.
Raises:
FolderValidationError: If validation fails.
DatabaseError: If there's a database error.
"""
logger.debug(f"Creating folder '{name}' for user #{user_id}")
try:
# Validate operation
await validate_folder_operation(
folder_id=None,
target_parent_id=parent_id,
user_id=user_id,
)
# Verify parent exists if provided
if parent_id:
parent = await prisma.models.LibraryFolder.prisma().find_first(
where={
"id": parent_id,
"userId": user_id,
"isDeleted": False,
}
)
if not parent:
raise NotFoundError(f"Parent folder #{parent_id} not found")
# Build data dict conditionally - don't include Parent key if no parent_id
create_data: dict = {
"name": name,
"User": {"connect": {"id": user_id}},
}
if icon is not None:
create_data["icon"] = icon
if color is not None:
create_data["color"] = color
if parent_id:
create_data["Parent"] = {"connect": {"id": parent_id}}
folder = await prisma.models.LibraryFolder.prisma().create(data=create_data)
return library_model.LibraryFolder.from_db(folder)
except prisma.errors.UniqueViolationError:
raise FolderValidationError(
"A folder with this name already exists in this location"
)
except prisma.errors.PrismaError as e:
logger.error(f"Database error creating folder: {e}")
raise DatabaseError("Failed to create folder") from e
async def create_folder_with_unique_name(
user_id: str,
base_name: str,
parent_id: Optional[str] = None,
icon: Optional[str] = None,
color: Optional[str] = None,
) -> library_model.LibraryFolder:
"""
Creates a folder, appending (2), (3), etc. if name exists.
Args:
user_id: The ID of the user.
base_name: The base folder name.
parent_id: Optional parent folder ID.
icon: Optional icon identifier.
color: Optional hex color code.
Returns:
The created LibraryFolder.
"""
name = base_name
suffix = 1
while True:
try:
return await create_folder(
user_id=user_id,
name=name,
parent_id=parent_id,
icon=icon,
color=color,
)
except FolderValidationError as e:
if "already exists" in str(e):
suffix += 1
name = f"{base_name} ({suffix})"
else:
raise
async def update_folder(
folder_id: str,
user_id: str,
name: Optional[str] = None,
icon: Optional[str] = None,
color: Optional[str] = None,
) -> library_model.LibraryFolder:
"""
Updates a folder's properties.
Args:
folder_id: The ID of the folder to update.
user_id: The ID of the user.
name: New folder name.
icon: New icon identifier.
color: New hex color code.
Returns:
The updated LibraryFolder.
Raises:
NotFoundError: If the folder doesn't exist.
DatabaseError: If there's a database error.
"""
logger.debug(f"Updating folder #{folder_id} for user #{user_id}")
try:
# Verify folder exists and belongs to user
existing = await prisma.models.LibraryFolder.prisma().find_first(
where={
"id": folder_id,
"userId": user_id,
"isDeleted": False,
}
)
if not existing:
raise NotFoundError(f"Folder #{folder_id} not found")
update_data: prisma.types.LibraryFolderUpdateInput = {}
if name is not None:
update_data["name"] = name
if icon is not None:
update_data["icon"] = icon
if color is not None:
update_data["color"] = color
if not update_data:
return await get_folder(folder_id, user_id)
folder = await prisma.models.LibraryFolder.prisma().update(
where={"id": folder_id},
data=update_data,
include={
"LibraryAgents": {"where": {"isDeleted": False}},
"Children": {"where": {"isDeleted": False}},
},
)
if not folder:
raise NotFoundError(f"Folder #{folder_id} not found")
agent_count = len(folder.LibraryAgents) if folder.LibraryAgents else 0
subfolder_count = len(folder.Children) if folder.Children else 0
return library_model.LibraryFolder.from_db(
folder,
agent_count=agent_count,
subfolder_count=subfolder_count,
)
except prisma.errors.UniqueViolationError:
raise FolderValidationError(
"A folder with this name already exists in this location"
)
except prisma.errors.PrismaError as e:
logger.error(f"Database error updating folder: {e}")
raise DatabaseError("Failed to update folder") from e
async def move_folder(
folder_id: str,
user_id: str,
target_parent_id: Optional[str],
) -> library_model.LibraryFolder:
"""
Moves a folder to a new parent.
Args:
folder_id: The ID of the folder to move.
user_id: The ID of the user.
target_parent_id: The target parent ID (None for root).
Returns:
The moved LibraryFolder.
Raises:
FolderValidationError: If the move is invalid.
NotFoundError: If the folder doesn't exist.
DatabaseError: If there's a database error.
"""
logger.debug(f"Moving folder #{folder_id} to parent #{target_parent_id}")
try:
# Validate operation
await validate_folder_operation(
folder_id=folder_id,
target_parent_id=target_parent_id,
user_id=user_id,
)
# Verify folder exists
existing = await prisma.models.LibraryFolder.prisma().find_first(
where={
"id": folder_id,
"userId": user_id,
"isDeleted": False,
}
)
if not existing:
raise NotFoundError(f"Folder #{folder_id} not found")
# Verify target parent exists if provided
if target_parent_id:
parent = await prisma.models.LibraryFolder.prisma().find_first(
where={
"id": target_parent_id,
"userId": user_id,
"isDeleted": False,
}
)
if not parent:
raise NotFoundError(
f"Target parent folder #{target_parent_id} not found"
)
folder = await prisma.models.LibraryFolder.prisma().update(
where={"id": folder_id},
data={
"parentId": target_parent_id,
},
include={
"LibraryAgents": {"where": {"isDeleted": False}},
"Children": {"where": {"isDeleted": False}},
},
)
if not folder:
raise NotFoundError(f"Folder #{folder_id} not found")
agent_count = len(folder.LibraryAgents) if folder.LibraryAgents else 0
subfolder_count = len(folder.Children) if folder.Children else 0
return library_model.LibraryFolder.from_db(
folder,
agent_count=agent_count,
subfolder_count=subfolder_count,
)
except prisma.errors.UniqueViolationError:
raise FolderValidationError(
"A folder with this name already exists in this location"
)
except prisma.errors.PrismaError as e:
logger.error(f"Database error moving folder: {e}")
raise DatabaseError("Failed to move folder") from e
async def delete_folder(
folder_id: str,
user_id: str,
soft_delete: bool = True,
) -> None:
"""
Deletes a folder and all its contents (cascade).
Args:
folder_id: The ID of the folder to delete.
user_id: The ID of the user.
soft_delete: If True, soft-deletes; otherwise hard-deletes.
Raises:
NotFoundError: If the folder doesn't exist.
DatabaseError: If there's a database error.
"""
logger.debug(f"Deleting folder #{folder_id} for user #{user_id}")
try:
# Verify folder exists
existing = await prisma.models.LibraryFolder.prisma().find_first(
where={
"id": folder_id,
"userId": user_id,
"isDeleted": False,
}
)
if not existing:
raise NotFoundError(f"Folder #{folder_id} not found")
async with transaction() as tx:
# Get all descendant folders recursively
descendant_ids = await _get_descendant_folder_ids(folder_id, user_id, tx)
all_folder_ids = [folder_id] + descendant_ids
if soft_delete:
# Soft-delete all agents in these folders
await prisma.models.LibraryAgent.prisma(tx).update_many(
where={
"folderId": {"in": all_folder_ids},
"userId": user_id,
},
data={"isDeleted": True},
)
# Soft-delete all folders
await prisma.models.LibraryFolder.prisma(tx).update_many(
where={
"id": {"in": all_folder_ids},
"userId": user_id,
},
data={"isDeleted": True},
)
else:
# Move agents to root (or could hard-delete them)
await prisma.models.LibraryAgent.prisma(tx).update_many(
where={
"folderId": {"in": all_folder_ids},
"userId": user_id,
},
data={"folderId": None},
)
# Hard-delete folders (children first due to FK constraints)
for fid in reversed(all_folder_ids):
await prisma.models.LibraryFolder.prisma(tx).delete(
where={"id": fid}
)
except prisma.errors.PrismaError as e:
logger.error(f"Database error deleting folder: {e}")
raise DatabaseError("Failed to delete folder") from e
async def _get_descendant_folder_ids(
folder_id: str,
user_id: str,
tx: Optional[prisma.Prisma] = None,
) -> list[str]:
"""
Recursively get all descendant folder IDs.
Args:
folder_id: The ID of the parent folder.
user_id: The ID of the user.
tx: Optional transaction.
Returns:
A list of descendant folder IDs.
"""
prisma_client = prisma.models.LibraryFolder.prisma(tx)
children = await prisma_client.find_many(
where={
"parentId": folder_id,
"userId": user_id,
"isDeleted": False,
}
)
result: list[str] = []
for child in children:
result.append(child.id)
result.extend(await _get_descendant_folder_ids(child.id, user_id, tx))
return result
async def move_agent_to_folder(
library_agent_id: str,
folder_id: Optional[str],
user_id: str,
) -> library_model.LibraryAgent:
"""
Moves a library agent to a folder.
Args:
library_agent_id: The ID of the library agent.
folder_id: The target folder ID (None for root).
user_id: The ID of the user.
Returns:
The updated LibraryAgent.
Raises:
NotFoundError: If the agent or folder doesn't exist.
DatabaseError: If there's a database error.
"""
logger.debug(f"Moving agent #{library_agent_id} to folder #{folder_id}")
try:
# Verify agent exists
agent = await prisma.models.LibraryAgent.prisma().find_first(
where={
"id": library_agent_id,
"userId": user_id,
"isDeleted": False,
}
)
if not agent:
raise NotFoundError(f"Library agent #{library_agent_id} not found")
# Verify folder exists if provided
if folder_id:
folder = await prisma.models.LibraryFolder.prisma().find_first(
where={
"id": folder_id,
"userId": user_id,
"isDeleted": False,
}
)
if not folder:
raise NotFoundError(f"Folder #{folder_id} not found")
await prisma.models.LibraryAgent.prisma().update(
where={"id": library_agent_id},
data={"folderId": folder_id},
)
return await get_library_agent(library_agent_id, user_id)
except prisma.errors.PrismaError as e:
logger.error(f"Database error moving agent to folder: {e}")
raise DatabaseError("Failed to move agent to folder") from e
async def bulk_move_agents_to_folder(
agent_ids: list[str],
folder_id: Optional[str],
user_id: str,
) -> list[library_model.LibraryAgent]:
"""
Moves multiple library agents to a folder.
Args:
agent_ids: The IDs of the library agents.
folder_id: The target folder ID (None for root).
user_id: The ID of the user.
Returns:
The updated LibraryAgents.
Raises:
NotFoundError: If any agent or the folder doesn't exist.
DatabaseError: If there's a database error.
"""
logger.debug(f"Bulk moving {len(agent_ids)} agents to folder #{folder_id}")
try:
# Verify folder exists if provided
if folder_id:
folder = await prisma.models.LibraryFolder.prisma().find_first(
where={
"id": folder_id,
"userId": user_id,
"isDeleted": False,
}
)
if not folder:
raise NotFoundError(f"Folder #{folder_id} not found")
# Update all agents
await prisma.models.LibraryAgent.prisma().update_many(
where={
"id": {"in": agent_ids},
"userId": user_id,
"isDeleted": False,
},
data={"folderId": folder_id},
)
# Fetch and return updated agents
agents = await prisma.models.LibraryAgent.prisma().find_many(
where={
"id": {"in": agent_ids},
"userId": user_id,
},
include=library_agent_include(
user_id, include_nodes=False, include_executions=False
),
)
return [library_model.LibraryAgent.from_db(agent) for agent in agents]
except prisma.errors.PrismaError as e:
logger.error(f"Database error bulk moving agents to folder: {e}")
raise DatabaseError("Failed to bulk move agents to folder") from e
##############################################
########### Presets DB Functions #############
##############################################
@@ -1919,7 +1130,7 @@ async def create_preset_from_graph_execution(
async def update_preset(
user_id: str,
preset_id: str,
inputs: Optional[GraphInput] = None,
inputs: Optional[BlockInput] = None,
credentials: Optional[dict[str, CredentialsMetaInput]] = None,
name: Optional[str] = None,
description: Optional[str] = None,

View File

@@ -1,4 +0,0 @@
class FolderValidationError(Exception):
"""Raised when folder operations fail validation."""
pass

View File

@@ -6,12 +6,9 @@ import prisma.enums
import prisma.models
import pydantic
from backend.data.block import BlockInput
from backend.data.graph import GraphModel, GraphSettings, GraphTriggerInfo
from backend.data.model import (
CredentialsMetaInput,
GraphInput,
is_credentials_field_name,
)
from backend.data.model import CredentialsMetaInput, is_credentials_field_name
from backend.util.json import loads as json_loads
from backend.util.models import Pagination
@@ -26,95 +23,6 @@ class LibraryAgentStatus(str, Enum):
ERROR = "ERROR"
# === Folder Models ===
class LibraryFolder(pydantic.BaseModel):
"""Represents a folder for organizing library agents."""
id: str
user_id: str
name: str
icon: str | None = None
color: str | None = None
parent_id: str | None = None
created_at: datetime.datetime
updated_at: datetime.datetime
agent_count: int = 0 # Direct agents in folder
subfolder_count: int = 0 # Direct child folders
@staticmethod
def from_db(
folder: prisma.models.LibraryFolder,
agent_count: int = 0,
subfolder_count: int = 0,
) -> "LibraryFolder":
"""Factory method that constructs a LibraryFolder from a Prisma model."""
return LibraryFolder(
id=folder.id,
user_id=folder.userId,
name=folder.name,
icon=folder.icon,
color=folder.color,
parent_id=folder.parentId,
created_at=folder.createdAt,
updated_at=folder.updatedAt,
agent_count=agent_count,
subfolder_count=subfolder_count,
)
class LibraryFolderTree(LibraryFolder):
"""Folder with nested children for tree view."""
children: list["LibraryFolderTree"] = []
class FolderCreateRequest(pydantic.BaseModel):
"""Request model for creating a folder."""
name: str = pydantic.Field(..., min_length=1, max_length=100)
icon: str | None = None
color: str | None = pydantic.Field(
None, pattern=r"^#[0-9A-Fa-f]{6}$", description="Hex color code (#RRGGBB)"
)
parent_id: str | None = None
class FolderUpdateRequest(pydantic.BaseModel):
"""Request model for updating a folder."""
name: str | None = pydantic.Field(None, min_length=1, max_length=100)
icon: str | None = None
color: str | None = None
class FolderMoveRequest(pydantic.BaseModel):
"""Request model for moving a folder to a new parent."""
target_parent_id: str | None = None # None = move to root
class BulkMoveAgentsRequest(pydantic.BaseModel):
"""Request model for moving multiple agents to a folder."""
agent_ids: list[str]
folder_id: str | None = None # None = move to root
class FolderListResponse(pydantic.BaseModel):
"""Response schema for a list of folders."""
folders: list[LibraryFolder]
pagination: Pagination
class FolderTreeResponse(pydantic.BaseModel):
"""Response schema for folder tree structure."""
tree: list[LibraryFolderTree]
class MarketplaceListingCreator(pydantic.BaseModel):
"""Creator information for a marketplace listing."""
@@ -209,9 +117,6 @@ class LibraryAgent(pydantic.BaseModel):
can_access_graph: bool
is_latest_version: bool
is_favorite: bool
folder_id: str | None = None
folder_name: str | None = None # Denormalized for display
recommended_schedule_cron: str | None = None
settings: GraphSettings = pydantic.Field(default_factory=GraphSettings)
marketplace_listing: Optional["MarketplaceListing"] = None
@@ -320,10 +225,6 @@ class LibraryAgent(pydantic.BaseModel):
creator=creator_data,
)
# Folder information
folder_id = agent.folderId
folder_name = agent.Folder.name if agent.Folder else None
return LibraryAgent(
id=agent.id,
graph_id=agent.agentGraphId,
@@ -355,8 +256,6 @@ class LibraryAgent(pydantic.BaseModel):
can_access_graph=can_access_graph,
is_latest_version=is_latest_version,
is_favorite=agent.isFavorite,
folder_id=folder_id,
folder_name=folder_name,
recommended_schedule_cron=agent.AgentGraph.recommendedScheduleCron,
settings=_parse_settings(agent.settings),
marketplace_listing=marketplace_listing_data,
@@ -424,7 +323,7 @@ class LibraryAgentPresetCreatable(pydantic.BaseModel):
graph_id: str
graph_version: int
inputs: GraphInput
inputs: BlockInput
credentials: dict[str, CredentialsMetaInput]
name: str
@@ -453,7 +352,7 @@ class LibraryAgentPresetUpdatable(pydantic.BaseModel):
Request model used when updating a preset for a library agent.
"""
inputs: Optional[GraphInput] = None
inputs: Optional[BlockInput] = None
credentials: Optional[dict[str, CredentialsMetaInput]] = None
name: Optional[str] = None
@@ -496,7 +395,7 @@ class LibraryAgentPreset(LibraryAgentPresetCreatable):
"Webhook must be included in AgentPreset query when webhookId is set"
)
input_data: GraphInput = {}
input_data: BlockInput = {}
input_credentials: dict[str, CredentialsMetaInput] = {}
for preset_input in preset.InputPresets:
@@ -568,7 +467,3 @@ class LibraryAgentUpdateRequest(pydantic.BaseModel):
settings: Optional[GraphSettings] = pydantic.Field(
default=None, description="User-specific settings for this library agent"
)
folder_id: Optional[str] = pydantic.Field(
default=None,
description="Folder ID to move agent to (empty string for root)",
)

View File

@@ -1,11 +1,9 @@
import fastapi
from .agents import router as agents_router
from .folders import router as folders_router
from .presets import router as presets_router
router = fastapi.APIRouter()
router.include_router(presets_router)
router.include_router(folders_router)
router.include_router(agents_router)

View File

@@ -41,34 +41,17 @@ async def list_library_agents(
ge=1,
description="Number of agents per page (must be >= 1)",
),
folder_id: Optional[str] = Query(
None,
description="Filter by folder ID",
),
include_root_only: bool = Query(
False,
description="Only return agents without a folder (root-level agents)",
),
) -> library_model.LibraryAgentResponse:
"""
Get all agents in the user's library (both created and saved).
"""
try:
return await library_db.list_library_agents(
user_id=user_id,
search_term=search_term,
sort_by=sort_by,
page=page,
page_size=page_size,
folder_id=folder_id,
include_root_only=include_root_only,
)
except Exception as e:
logger.error(f"Could not list library agents for user #{user_id}: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(e),
) from e
return await library_db.list_library_agents(
user_id=user_id,
search_term=search_term,
sort_by=sort_by,
page=page,
page_size=page_size,
)
@router.get(
@@ -177,34 +160,15 @@ async def update_library_agent(
"""
Update the library agent with the given fields.
"""
try:
return await library_db.update_library_agent(
library_agent_id=library_agent_id,
user_id=user_id,
auto_update_version=payload.auto_update_version,
graph_version=payload.graph_version,
is_favorite=payload.is_favorite,
is_archived=payload.is_archived,
settings=payload.settings,
folder_id=payload.folder_id,
)
except NotFoundError as e:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=str(e),
) from e
except DatabaseError as e:
logger.error(f"Database error while updating library agent: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail={"message": str(e), "hint": "Verify DB connection."},
) from e
except Exception as e:
logger.error(f"Unexpected error while updating library agent: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail={"message": str(e), "hint": "Check server logs."},
) from e
return await library_db.update_library_agent(
library_agent_id=library_agent_id,
user_id=user_id,
auto_update_version=payload.auto_update_version,
graph_version=payload.graph_version,
is_favorite=payload.is_favorite,
is_archived=payload.is_archived,
settings=payload.settings,
)
@router.delete(

View File

@@ -1,408 +0,0 @@
import logging
from typing import Optional
import autogpt_libs.auth as autogpt_auth_lib
from fastapi import APIRouter, HTTPException, Query, Security, status
from fastapi.responses import Response
from backend.util.exceptions import DatabaseError, NotFoundError
from .. import db as library_db
from .. import model as library_model
logger = logging.getLogger(__name__)
router = APIRouter(
prefix="/folders",
tags=["library", "folders", "private"],
dependencies=[Security(autogpt_auth_lib.requires_user)],
)
@router.get(
"",
summary="List Library Folders",
response_model=library_model.FolderListResponse,
responses={
200: {"description": "List of folders"},
500: {"description": "Server error"},
},
)
async def list_folders(
user_id: str = Security(autogpt_auth_lib.get_user_id),
parent_id: Optional[str] = Query(
None,
description="Filter by parent folder ID. If not provided, returns root-level folders.",
),
include_counts: bool = Query(
True,
description="Include agent and subfolder counts",
),
) -> library_model.FolderListResponse:
"""
List folders for the authenticated user.
Args:
user_id: ID of the authenticated user.
parent_id: Optional parent folder ID to filter by.
include_counts: Whether to include agent and subfolder counts.
Returns:
A FolderListResponse containing folders.
"""
try:
folders = await library_db.list_folders(
user_id=user_id,
parent_id=parent_id,
include_counts=include_counts,
)
return library_model.FolderListResponse(
folders=folders,
pagination=library_model.Pagination(
total_items=len(folders),
total_pages=1,
current_page=1,
page_size=len(folders),
),
)
except Exception as e:
logger.error(f"Could not list folders for user #{user_id}: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(e),
) from e
@router.get(
"/tree",
summary="Get Folder Tree",
response_model=library_model.FolderTreeResponse,
responses={
200: {"description": "Folder tree structure"},
500: {"description": "Server error"},
},
)
async def get_folder_tree(
user_id: str = Security(autogpt_auth_lib.get_user_id),
) -> library_model.FolderTreeResponse:
"""
Get the full folder tree for the authenticated user.
Args:
user_id: ID of the authenticated user.
Returns:
A FolderTreeResponse containing the nested folder structure.
"""
try:
tree = await library_db.get_folder_tree(user_id=user_id)
return library_model.FolderTreeResponse(tree=tree)
except Exception as e:
logger.error(f"Could not get folder tree for user #{user_id}: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(e),
) from e
@router.get(
"/{folder_id}",
summary="Get Folder",
response_model=library_model.LibraryFolder,
responses={
200: {"description": "Folder details"},
404: {"description": "Folder not found"},
500: {"description": "Server error"},
},
)
async def get_folder(
folder_id: str,
user_id: str = Security(autogpt_auth_lib.get_user_id),
) -> library_model.LibraryFolder:
"""
Get a specific folder.
Args:
folder_id: ID of the folder to retrieve.
user_id: ID of the authenticated user.
Returns:
The requested LibraryFolder.
"""
try:
return await library_db.get_folder(folder_id=folder_id, user_id=user_id)
except NotFoundError as e:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=str(e),
) from e
except Exception as e:
logger.error(f"Could not get folder #{folder_id}: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(e),
) from e
@router.post(
"",
summary="Create Folder",
status_code=status.HTTP_201_CREATED,
response_model=library_model.LibraryFolder,
responses={
201: {"description": "Folder created successfully"},
400: {"description": "Validation error"},
404: {"description": "Parent folder not found"},
409: {"description": "Folder name conflict"},
500: {"description": "Server error"},
},
)
async def create_folder(
payload: library_model.FolderCreateRequest,
user_id: str = Security(autogpt_auth_lib.get_user_id),
) -> library_model.LibraryFolder:
"""
Create a new folder.
Args:
payload: The folder creation request.
user_id: ID of the authenticated user.
Returns:
The created LibraryFolder.
"""
try:
return await library_db.create_folder(
user_id=user_id,
name=payload.name,
parent_id=payload.parent_id,
icon=payload.icon,
color=payload.color,
)
except library_db.FolderValidationError as e:
if "already exists" in str(e):
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=str(e),
) from e
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=str(e),
) from e
except NotFoundError as e:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=str(e),
) from e
except DatabaseError as e:
logger.error(f"Database error creating folder: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(e),
) from e
@router.patch(
"/{folder_id}",
summary="Update Folder",
response_model=library_model.LibraryFolder,
responses={
200: {"description": "Folder updated successfully"},
400: {"description": "Validation error"},
404: {"description": "Folder not found"},
409: {"description": "Folder name conflict"},
500: {"description": "Server error"},
},
)
async def update_folder(
folder_id: str,
payload: library_model.FolderUpdateRequest,
user_id: str = Security(autogpt_auth_lib.get_user_id),
) -> library_model.LibraryFolder:
"""
Update a folder's properties.
Args:
folder_id: ID of the folder to update.
payload: The folder update request.
user_id: ID of the authenticated user.
Returns:
The updated LibraryFolder.
"""
try:
return await library_db.update_folder(
folder_id=folder_id,
user_id=user_id,
name=payload.name,
icon=payload.icon,
color=payload.color,
)
except library_db.FolderValidationError as e:
if "already exists" in str(e):
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=str(e),
) from e
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=str(e),
) from e
except NotFoundError as e:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=str(e),
) from e
except DatabaseError as e:
logger.error(f"Database error updating folder #{folder_id}: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(e),
) from e
@router.post(
"/{folder_id}/move",
summary="Move Folder",
response_model=library_model.LibraryFolder,
responses={
200: {"description": "Folder moved successfully"},
400: {"description": "Validation error (circular reference, depth exceeded)"},
404: {"description": "Folder or target parent not found"},
409: {"description": "Folder name conflict in target location"},
500: {"description": "Server error"},
},
)
async def move_folder(
folder_id: str,
payload: library_model.FolderMoveRequest,
user_id: str = Security(autogpt_auth_lib.get_user_id),
) -> library_model.LibraryFolder:
"""
Move a folder to a new parent.
Args:
folder_id: ID of the folder to move.
payload: The move request with target parent.
user_id: ID of the authenticated user.
Returns:
The moved LibraryFolder.
"""
try:
return await library_db.move_folder(
folder_id=folder_id,
user_id=user_id,
target_parent_id=payload.target_parent_id,
)
except library_db.FolderValidationError as e:
if "already exists" in str(e):
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=str(e),
) from e
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=str(e),
) from e
except NotFoundError as e:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=str(e),
) from e
except DatabaseError as e:
logger.error(f"Database error moving folder #{folder_id}: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(e),
) from e
@router.delete(
"/{folder_id}",
summary="Delete Folder",
status_code=status.HTTP_204_NO_CONTENT,
responses={
204: {"description": "Folder deleted successfully"},
404: {"description": "Folder not found"},
500: {"description": "Server error"},
},
)
async def delete_folder(
folder_id: str,
user_id: str = Security(autogpt_auth_lib.get_user_id),
) -> Response:
"""
Soft-delete a folder and all its contents.
Args:
folder_id: ID of the folder to delete.
user_id: ID of the authenticated user.
Returns:
204 No Content if successful.
"""
try:
await library_db.delete_folder(
folder_id=folder_id,
user_id=user_id,
soft_delete=True,
)
return Response(status_code=status.HTTP_204_NO_CONTENT)
except NotFoundError as e:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=str(e),
) from e
except DatabaseError as e:
logger.error(f"Database error deleting folder #{folder_id}: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(e),
) from e
# === Bulk Agent Operations ===
@router.post(
"/agents/bulk-move",
summary="Bulk Move Agents",
response_model=list[library_model.LibraryAgent],
responses={
200: {"description": "Agents moved successfully"},
404: {"description": "Folder not found"},
500: {"description": "Server error"},
},
)
async def bulk_move_agents(
payload: library_model.BulkMoveAgentsRequest,
user_id: str = Security(autogpt_auth_lib.get_user_id),
) -> list[library_model.LibraryAgent]:
"""
Move multiple agents to a folder.
Args:
payload: The bulk move request with agent IDs and target folder.
user_id: ID of the authenticated user.
Returns:
The updated LibraryAgents.
"""
try:
return await library_db.bulk_move_agents_to_folder(
agent_ids=payload.agent_ids,
folder_id=payload.folder_id,
user_id=user_id,
)
except NotFoundError as e:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=str(e),
) from e
except DatabaseError as e:
logger.error(f"Database error bulk moving agents: {e}")
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=str(e),
) from e

View File

@@ -5,8 +5,8 @@ from typing import Optional
import aiohttp
from fastapi import HTTPException
from backend.blocks import get_block
from backend.data import graph as graph_db
from backend.data.block import get_block
from backend.util.settings import Settings
from .models import ApiResponse, ChatRequest, GraphData

View File

@@ -152,7 +152,7 @@ class BlockHandler(ContentHandler):
async def get_missing_items(self, batch_size: int) -> list[ContentItem]:
"""Fetch blocks without embeddings."""
from backend.blocks import get_blocks
from backend.data.block import get_blocks
# Get all available blocks
all_blocks = get_blocks()
@@ -249,7 +249,7 @@ class BlockHandler(ContentHandler):
async def get_stats(self) -> dict[str, int]:
"""Get statistics about block embedding coverage."""
from backend.blocks import get_blocks
from backend.data.block import get_blocks
all_blocks = get_blocks()

View File

@@ -93,7 +93,7 @@ async def test_block_handler_get_missing_items(mocker):
mock_existing = []
with patch(
"backend.blocks.get_blocks",
"backend.data.block.get_blocks",
return_value=mock_blocks,
):
with patch(
@@ -135,7 +135,7 @@ async def test_block_handler_get_stats(mocker):
mock_embedded = [{"count": 2}]
with patch(
"backend.blocks.get_blocks",
"backend.data.block.get_blocks",
return_value=mock_blocks,
):
with patch(
@@ -327,7 +327,7 @@ async def test_block_handler_handles_missing_attributes():
mock_blocks = {"block-minimal": mock_block_class}
with patch(
"backend.blocks.get_blocks",
"backend.data.block.get_blocks",
return_value=mock_blocks,
):
with patch(
@@ -360,7 +360,7 @@ async def test_block_handler_skips_failed_blocks():
mock_blocks = {"good-block": good_block, "bad-block": bad_block}
with patch(
"backend.blocks.get_blocks",
"backend.data.block.get_blocks",
return_value=mock_blocks,
):
with patch(

View File

@@ -662,7 +662,7 @@ async def cleanup_orphaned_embeddings() -> dict[str, Any]:
)
current_ids = {row["id"] for row in valid_agents}
elif content_type == ContentType.BLOCK:
from backend.blocks import get_blocks
from backend.data.block import get_blocks
current_ids = set(get_blocks().keys())
elif content_type == ContentType.DOCUMENTATION:

View File

@@ -8,7 +8,6 @@ Includes BM25 reranking for improved lexical relevance.
import logging
import re
import time
from dataclasses import dataclass
from typing import Any, Literal
@@ -363,11 +362,7 @@ async def unified_hybrid_search(
LIMIT {limit_param} OFFSET {offset_param}
"""
try:
results = await query_raw_with_schema(sql_query, *params)
except Exception as e:
await _log_vector_error_diagnostics(e)
raise
results = await query_raw_with_schema(sql_query, *params)
total = results[0]["total_count"] if results else 0
# Apply BM25 reranking
@@ -691,11 +686,7 @@ async def hybrid_search(
LIMIT {limit_param} OFFSET {offset_param}
"""
try:
results = await query_raw_with_schema(sql_query, *params)
except Exception as e:
await _log_vector_error_diagnostics(e)
raise
results = await query_raw_with_schema(sql_query, *params)
total = results[0]["total_count"] if results else 0
@@ -727,87 +718,6 @@ async def hybrid_search_simple(
return await hybrid_search(query=query, page=page, page_size=page_size)
# ============================================================================
# Diagnostics
# ============================================================================
# Rate limit: only log vector error diagnostics once per this interval
_VECTOR_DIAG_INTERVAL_SECONDS = 60
_last_vector_diag_time: float = 0
async def _log_vector_error_diagnostics(error: Exception) -> None:
"""Log diagnostic info when 'type vector does not exist' error occurs.
Note: Diagnostic queries use query_raw_with_schema which may run on a different
pooled connection than the one that failed. Session-level search_path can differ,
so these diagnostics show cluster-wide state, not necessarily the failed session.
Includes rate limiting to avoid log spam - only logs once per minute.
Caller should re-raise the error after calling this function.
"""
global _last_vector_diag_time
# Check if this is the vector type error
error_str = str(error).lower()
if not (
"type" in error_str and "vector" in error_str and "does not exist" in error_str
):
return
# Rate limit: only log once per interval
now = time.time()
if now - _last_vector_diag_time < _VECTOR_DIAG_INTERVAL_SECONDS:
return
_last_vector_diag_time = now
try:
diagnostics: dict[str, object] = {}
try:
search_path_result = await query_raw_with_schema("SHOW search_path")
diagnostics["search_path"] = search_path_result
except Exception as e:
diagnostics["search_path"] = f"Error: {e}"
try:
schema_result = await query_raw_with_schema("SELECT current_schema()")
diagnostics["current_schema"] = schema_result
except Exception as e:
diagnostics["current_schema"] = f"Error: {e}"
try:
user_result = await query_raw_with_schema(
"SELECT current_user, session_user, current_database()"
)
diagnostics["user_info"] = user_result
except Exception as e:
diagnostics["user_info"] = f"Error: {e}"
try:
# Check pgvector extension installation (cluster-wide, stable info)
ext_result = await query_raw_with_schema(
"SELECT extname, extversion, nspname as schema "
"FROM pg_extension e "
"JOIN pg_namespace n ON e.extnamespace = n.oid "
"WHERE extname = 'vector'"
)
diagnostics["pgvector_extension"] = ext_result
except Exception as e:
diagnostics["pgvector_extension"] = f"Error: {e}"
logger.error(
f"Vector type error diagnostics:\n"
f" Error: {error}\n"
f" search_path: {diagnostics.get('search_path')}\n"
f" current_schema: {diagnostics.get('current_schema')}\n"
f" user_info: {diagnostics.get('user_info')}\n"
f" pgvector_extension: {diagnostics.get('pgvector_extension')}"
)
except Exception as diag_error:
logger.error(f"Failed to collect vector error diagnostics: {diag_error}")
# Backward compatibility alias - HybridSearchWeights maps to StoreAgentSearchWeights
# for existing code that expects the popularity parameter
HybridSearchWeights = StoreAgentSearchWeights

View File

@@ -7,6 +7,15 @@ from replicate.client import Client as ReplicateClient
from replicate.exceptions import ReplicateError
from replicate.helpers import FileOutput
from backend.blocks.ideogram import (
AspectRatio,
ColorPalettePreset,
IdeogramModelBlock,
IdeogramModelName,
MagicPromptOption,
StyleType,
UpscaleOption,
)
from backend.data.graph import GraphBaseMeta
from backend.data.model import CredentialsMetaInput, ProviderName
from backend.integrations.credentials_store import ideogram_credentials
@@ -41,16 +50,6 @@ async def generate_agent_image_v2(graph: GraphBaseMeta | AgentGraph) -> io.Bytes
if not ideogram_credentials.api_key:
raise ValueError("Missing Ideogram API key")
from backend.blocks.ideogram import (
AspectRatio,
ColorPalettePreset,
IdeogramModelBlock,
IdeogramModelName,
MagicPromptOption,
StyleType,
UpscaleOption,
)
name = graph.name
description = f"{name} ({graph.description})" if graph.description else name

View File

@@ -40,11 +40,10 @@ from backend.api.model import (
UpdateTimezoneRequest,
UploadFileResponse,
)
from backend.blocks import get_block, get_blocks
from backend.data import execution as execution_db
from backend.data import graph as graph_db
from backend.data.auth import api_key as api_key_db
from backend.data.block import BlockInput, CompletedBlockOutput
from backend.data.block import BlockInput, CompletedBlockOutput, get_block, get_blocks
from backend.data.credit import (
AutoTopUpConfig,
RefundRequest,
@@ -828,7 +827,28 @@ async def update_graph(
existing_versions = await graph_db.get_graph_all_versions(graph_id, user_id=user_id)
if not existing_versions:
raise HTTPException(404, detail=f"Graph #{graph_id} not found")
# User doesn't own this graph -- check if they have it in their library
# (e.g. added from the marketplace). If so, fork it and apply their edits.
library_agent = await library_db.get_library_agent_by_graph_id(
user_id=user_id, graph_id=graph_id
)
if not library_agent:
raise HTTPException(404, detail=f"Graph #{graph_id} not found")
# Fork the marketplace agent to create a user-owned copy
forked = await graph_db.fork_graph(
graph_id, library_agent.graph_version, user_id
)
forked = await on_graph_activate(forked, user_id=user_id)
await graph_db.set_graph_active_version(
graph_id=forked.id, version=forked.version, user_id=user_id
)
await library_db.create_library_agent(forked, user_id)
# Apply the user's edits on top of the fork via the normal update path
graph_id = forked.id
graph.id = forked.id
existing_versions = [forked]
graph.version = max(g.version for g in existing_versions) + 1
current_active_version = next((v for v in existing_versions if v.is_active), None)

View File

@@ -3,19 +3,22 @@ import logging
import os
import re
from pathlib import Path
from typing import Sequence, Type, TypeVar
from typing import TYPE_CHECKING, TypeVar
from backend.blocks._base import AnyBlockSchema, BlockType
from backend.util.cache import cached
logger = logging.getLogger(__name__)
if TYPE_CHECKING:
from backend.data.block import Block
T = TypeVar("T")
@cached(ttl_seconds=3600)
def load_all_blocks() -> dict[str, type["AnyBlockSchema"]]:
from backend.blocks._base import Block
def load_all_blocks() -> dict[str, type["Block"]]:
from backend.data.block import Block
from backend.util.settings import Config
# Check if example blocks should be loaded from settings
@@ -47,8 +50,8 @@ def load_all_blocks() -> dict[str, type["AnyBlockSchema"]]:
importlib.import_module(f".{module}", package=__name__)
# Load all Block instances from the available modules
available_blocks: dict[str, type["AnyBlockSchema"]] = {}
for block_cls in _all_subclasses(Block):
available_blocks: dict[str, type["Block"]] = {}
for block_cls in all_subclasses(Block):
class_name = block_cls.__name__
if class_name.endswith("Base"):
@@ -61,7 +64,7 @@ def load_all_blocks() -> dict[str, type["AnyBlockSchema"]]:
"please name the class with 'Base' at the end"
)
block = block_cls() # pyright: ignore[reportAbstractUsage]
block = block_cls.create()
if not isinstance(block.id, str) or len(block.id) != 36:
raise ValueError(
@@ -102,7 +105,7 @@ def load_all_blocks() -> dict[str, type["AnyBlockSchema"]]:
available_blocks[block.id] = block_cls
# Filter out blocks with incomplete auth configs, e.g. missing OAuth server secrets
from ._utils import is_block_auth_configured
from backend.data.block import is_block_auth_configured
filtered_blocks = {}
for block_id, block_cls in available_blocks.items():
@@ -112,48 +115,11 @@ def load_all_blocks() -> dict[str, type["AnyBlockSchema"]]:
return filtered_blocks
def _all_subclasses(cls: type[T]) -> list[type[T]]:
__all__ = ["load_all_blocks"]
def all_subclasses(cls: type[T]) -> list[type[T]]:
subclasses = cls.__subclasses__()
for subclass in subclasses:
subclasses += _all_subclasses(subclass)
subclasses += all_subclasses(subclass)
return subclasses
# ============== Block access helper functions ============== #
def get_blocks() -> dict[str, Type["AnyBlockSchema"]]:
return load_all_blocks()
# Note on the return type annotation: https://github.com/microsoft/pyright/issues/10281
def get_block(block_id: str) -> "AnyBlockSchema | None":
cls = get_blocks().get(block_id)
return cls() if cls else None
@cached(ttl_seconds=3600)
def get_webhook_block_ids() -> Sequence[str]:
return [
id
for id, B in get_blocks().items()
if B().block_type in (BlockType.WEBHOOK, BlockType.WEBHOOK_MANUAL)
]
@cached(ttl_seconds=3600)
def get_io_block_ids() -> Sequence[str]:
return [
id
for id, B in get_blocks().items()
if B().block_type in (BlockType.INPUT, BlockType.OUTPUT)
]
@cached(ttl_seconds=3600)
def get_human_in_the_loop_block_ids() -> Sequence[str]:
return [
id
for id, B in get_blocks().items()
if B().block_type == BlockType.HUMAN_IN_THE_LOOP
]

View File

@@ -1,739 +0,0 @@
import inspect
import logging
from abc import ABC, abstractmethod
from enum import Enum
from typing import (
TYPE_CHECKING,
Any,
Callable,
ClassVar,
Generic,
Optional,
Type,
TypeAlias,
TypeVar,
cast,
get_origin,
)
import jsonref
import jsonschema
from pydantic import BaseModel
from backend.data.block import BlockInput, BlockOutput, BlockOutputEntry
from backend.data.model import (
Credentials,
CredentialsFieldInfo,
CredentialsMetaInput,
SchemaField,
is_credentials_field_name,
)
from backend.integrations.providers import ProviderName
from backend.util import json
from backend.util.exceptions import (
BlockError,
BlockExecutionError,
BlockInputError,
BlockOutputError,
BlockUnknownError,
)
from backend.util.settings import Config
logger = logging.getLogger(__name__)
if TYPE_CHECKING:
from backend.data.execution import ExecutionContext
from backend.data.model import ContributorDetails, NodeExecutionStats
from ..data.graph import Link
app_config = Config()
BlockTestOutput = BlockOutputEntry | tuple[str, Callable[[Any], bool]]
class BlockType(Enum):
STANDARD = "Standard"
INPUT = "Input"
OUTPUT = "Output"
NOTE = "Note"
WEBHOOK = "Webhook"
WEBHOOK_MANUAL = "Webhook (manual)"
AGENT = "Agent"
AI = "AI"
AYRSHARE = "Ayrshare"
HUMAN_IN_THE_LOOP = "Human In The Loop"
class BlockCategory(Enum):
AI = "Block that leverages AI to perform a task."
SOCIAL = "Block that interacts with social media platforms."
TEXT = "Block that processes text data."
SEARCH = "Block that searches or extracts information from the internet."
BASIC = "Block that performs basic operations."
INPUT = "Block that interacts with input of the graph."
OUTPUT = "Block that interacts with output of the graph."
LOGIC = "Programming logic to control the flow of your agent"
COMMUNICATION = "Block that interacts with communication platforms."
DEVELOPER_TOOLS = "Developer tools such as GitHub blocks."
DATA = "Block that interacts with structured data."
HARDWARE = "Block that interacts with hardware."
AGENT = "Block that interacts with other agents."
CRM = "Block that interacts with CRM services."
SAFETY = (
"Block that provides AI safety mechanisms such as detecting harmful content"
)
PRODUCTIVITY = "Block that helps with productivity"
ISSUE_TRACKING = "Block that helps with issue tracking"
MULTIMEDIA = "Block that interacts with multimedia content"
MARKETING = "Block that helps with marketing"
def dict(self) -> dict[str, str]:
return {"category": self.name, "description": self.value}
class BlockCostType(str, Enum):
RUN = "run" # cost X credits per run
BYTE = "byte" # cost X credits per byte
SECOND = "second" # cost X credits per second
class BlockCost(BaseModel):
cost_amount: int
cost_filter: BlockInput
cost_type: BlockCostType
def __init__(
self,
cost_amount: int,
cost_type: BlockCostType = BlockCostType.RUN,
cost_filter: Optional[BlockInput] = None,
**data: Any,
) -> None:
super().__init__(
cost_amount=cost_amount,
cost_filter=cost_filter or {},
cost_type=cost_type,
**data,
)
class BlockInfo(BaseModel):
id: str
name: str
inputSchema: dict[str, Any]
outputSchema: dict[str, Any]
costs: list[BlockCost]
description: str
categories: list[dict[str, str]]
contributors: list[dict[str, Any]]
staticOutput: bool
uiType: str
class BlockSchema(BaseModel):
cached_jsonschema: ClassVar[dict[str, Any]]
@classmethod
def jsonschema(cls) -> dict[str, Any]:
if cls.cached_jsonschema:
return cls.cached_jsonschema
model = jsonref.replace_refs(cls.model_json_schema(), merge_props=True)
def ref_to_dict(obj):
if isinstance(obj, dict):
# OpenAPI <3.1 does not support sibling fields that has a $ref key
# So sometimes, the schema has an "allOf"/"anyOf"/"oneOf" with 1 item.
keys = {"allOf", "anyOf", "oneOf"}
one_key = next((k for k in keys if k in obj and len(obj[k]) == 1), None)
if one_key:
obj.update(obj[one_key][0])
return {
key: ref_to_dict(value)
for key, value in obj.items()
if not key.startswith("$") and key != one_key
}
elif isinstance(obj, list):
return [ref_to_dict(item) for item in obj]
return obj
cls.cached_jsonschema = cast(dict[str, Any], ref_to_dict(model))
return cls.cached_jsonschema
@classmethod
def validate_data(cls, data: BlockInput) -> str | None:
return json.validate_with_jsonschema(
schema=cls.jsonschema(),
data={k: v for k, v in data.items() if v is not None},
)
@classmethod
def get_mismatch_error(cls, data: BlockInput) -> str | None:
return cls.validate_data(data)
@classmethod
def get_field_schema(cls, field_name: str) -> dict[str, Any]:
model_schema = cls.jsonschema().get("properties", {})
if not model_schema:
raise ValueError(f"Invalid model schema {cls}")
property_schema = model_schema.get(field_name)
if not property_schema:
raise ValueError(f"Invalid property name {field_name}")
return property_schema
@classmethod
def validate_field(cls, field_name: str, data: BlockInput) -> str | None:
"""
Validate the data against a specific property (one of the input/output name).
Returns the validation error message if the data does not match the schema.
"""
try:
property_schema = cls.get_field_schema(field_name)
jsonschema.validate(json.to_dict(data), property_schema)
return None
except jsonschema.ValidationError as e:
return str(e)
@classmethod
def get_fields(cls) -> set[str]:
return set(cls.model_fields.keys())
@classmethod
def get_required_fields(cls) -> set[str]:
return {
field
for field, field_info in cls.model_fields.items()
if field_info.is_required()
}
@classmethod
def __pydantic_init_subclass__(cls, **kwargs):
"""Validates the schema definition. Rules:
- Fields with annotation `CredentialsMetaInput` MUST be
named `credentials` or `*_credentials`
- Fields named `credentials` or `*_credentials` MUST be
of type `CredentialsMetaInput`
"""
super().__pydantic_init_subclass__(**kwargs)
# Reset cached JSON schema to prevent inheriting it from parent class
cls.cached_jsonschema = {}
credentials_fields = cls.get_credentials_fields()
for field_name in cls.get_fields():
if is_credentials_field_name(field_name):
if field_name not in credentials_fields:
raise TypeError(
f"Credentials field '{field_name}' on {cls.__qualname__} "
f"is not of type {CredentialsMetaInput.__name__}"
)
CredentialsMetaInput.validate_credentials_field_schema(
cls.get_field_schema(field_name), field_name
)
elif field_name in credentials_fields:
raise KeyError(
f"Credentials field '{field_name}' on {cls.__qualname__} "
"has invalid name: must be 'credentials' or *_credentials"
)
@classmethod
def get_credentials_fields(cls) -> dict[str, type[CredentialsMetaInput]]:
return {
field_name: info.annotation
for field_name, info in cls.model_fields.items()
if (
inspect.isclass(info.annotation)
and issubclass(
get_origin(info.annotation) or info.annotation,
CredentialsMetaInput,
)
)
}
@classmethod
def get_auto_credentials_fields(cls) -> dict[str, dict[str, Any]]:
"""
Get fields that have auto_credentials metadata (e.g., GoogleDriveFileInput).
Returns a dict mapping kwarg_name -> {field_name, auto_credentials_config}
Raises:
ValueError: If multiple fields have the same kwarg_name, as this would
cause silent overwriting and only the last field would be processed.
"""
result: dict[str, dict[str, Any]] = {}
schema = cls.jsonschema()
properties = schema.get("properties", {})
for field_name, field_schema in properties.items():
auto_creds = field_schema.get("auto_credentials")
if auto_creds:
kwarg_name = auto_creds.get("kwarg_name", "credentials")
if kwarg_name in result:
raise ValueError(
f"Duplicate auto_credentials kwarg_name '{kwarg_name}' "
f"in fields '{result[kwarg_name]['field_name']}' and "
f"'{field_name}' on {cls.__qualname__}"
)
result[kwarg_name] = {
"field_name": field_name,
"config": auto_creds,
}
return result
@classmethod
def get_credentials_fields_info(cls) -> dict[str, CredentialsFieldInfo]:
result = {}
# Regular credentials fields
for field_name in cls.get_credentials_fields().keys():
result[field_name] = CredentialsFieldInfo.model_validate(
cls.get_field_schema(field_name), by_alias=True
)
# Auto-generated credentials fields (from GoogleDriveFileInput etc.)
for kwarg_name, info in cls.get_auto_credentials_fields().items():
config = info["config"]
# Build a schema-like dict that CredentialsFieldInfo can parse
auto_schema = {
"credentials_provider": [config.get("provider", "google")],
"credentials_types": [config.get("type", "oauth2")],
"credentials_scopes": config.get("scopes"),
}
result[kwarg_name] = CredentialsFieldInfo.model_validate(
auto_schema, by_alias=True
)
return result
@classmethod
def get_input_defaults(cls, data: BlockInput) -> BlockInput:
return data # Return as is, by default.
@classmethod
def get_missing_links(cls, data: BlockInput, links: list["Link"]) -> set[str]:
input_fields_from_nodes = {link.sink_name for link in links}
return input_fields_from_nodes - set(data)
@classmethod
def get_missing_input(cls, data: BlockInput) -> set[str]:
return cls.get_required_fields() - set(data)
class BlockSchemaInput(BlockSchema):
"""
Base schema class for block inputs.
All block input schemas should extend this class for consistency.
"""
pass
class BlockSchemaOutput(BlockSchema):
"""
Base schema class for block outputs that includes a standard error field.
All block output schemas should extend this class to ensure consistent error handling.
"""
error: str = SchemaField(
description="Error message if the operation failed", default=""
)
BlockSchemaInputType = TypeVar("BlockSchemaInputType", bound=BlockSchemaInput)
BlockSchemaOutputType = TypeVar("BlockSchemaOutputType", bound=BlockSchemaOutput)
class EmptyInputSchema(BlockSchemaInput):
pass
class EmptyOutputSchema(BlockSchemaOutput):
pass
# For backward compatibility - will be deprecated
EmptySchema = EmptyOutputSchema
# --8<-- [start:BlockWebhookConfig]
class BlockManualWebhookConfig(BaseModel):
"""
Configuration model for webhook-triggered blocks on which
the user has to manually set up the webhook at the provider.
"""
provider: ProviderName
"""The service provider that the webhook connects to"""
webhook_type: str
"""
Identifier for the webhook type. E.g. GitHub has repo and organization level hooks.
Only for use in the corresponding `WebhooksManager`.
"""
event_filter_input: str = ""
"""
Name of the block's event filter input.
Leave empty if the corresponding webhook doesn't have distinct event/payload types.
"""
event_format: str = "{event}"
"""
Template string for the event(s) that a block instance subscribes to.
Applied individually to each event selected in the event filter input.
Example: `"pull_request.{event}"` -> `"pull_request.opened"`
"""
class BlockWebhookConfig(BlockManualWebhookConfig):
"""
Configuration model for webhook-triggered blocks for which
the webhook can be automatically set up through the provider's API.
"""
resource_format: str
"""
Template string for the resource that a block instance subscribes to.
Fields will be filled from the block's inputs (except `payload`).
Example: `f"{repo}/pull_requests"` (note: not how it's actually implemented)
Only for use in the corresponding `WebhooksManager`.
"""
# --8<-- [end:BlockWebhookConfig]
class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
def __init__(
self,
id: str = "",
description: str = "",
contributors: list["ContributorDetails"] = [],
categories: set[BlockCategory] | None = None,
input_schema: Type[BlockSchemaInputType] = EmptyInputSchema,
output_schema: Type[BlockSchemaOutputType] = EmptyOutputSchema,
test_input: BlockInput | list[BlockInput] | None = None,
test_output: BlockTestOutput | list[BlockTestOutput] | None = None,
test_mock: dict[str, Any] | None = None,
test_credentials: Optional[Credentials | dict[str, Credentials]] = None,
disabled: bool = False,
static_output: bool = False,
block_type: BlockType = BlockType.STANDARD,
webhook_config: Optional[BlockWebhookConfig | BlockManualWebhookConfig] = None,
is_sensitive_action: bool = False,
):
"""
Initialize the block with the given schema.
Args:
id: The unique identifier for the block, this value will be persisted in the
DB. So it should be a unique and constant across the application run.
Use the UUID format for the ID.
description: The description of the block, explaining what the block does.
contributors: The list of contributors who contributed to the block.
input_schema: The schema, defined as a Pydantic model, for the input data.
output_schema: The schema, defined as a Pydantic model, for the output data.
test_input: The list or single sample input data for the block, for testing.
test_output: The list or single expected output if the test_input is run.
test_mock: function names on the block implementation to mock on test run.
disabled: If the block is disabled, it will not be available for execution.
static_output: Whether the output links of the block are static by default.
"""
from backend.data.model import NodeExecutionStats
self.id = id
self.input_schema = input_schema
self.output_schema = output_schema
self.test_input = test_input
self.test_output = test_output
self.test_mock = test_mock
self.test_credentials = test_credentials
self.description = description
self.categories = categories or set()
self.contributors = contributors or set()
self.disabled = disabled
self.static_output = static_output
self.block_type = block_type
self.webhook_config = webhook_config
self.is_sensitive_action = is_sensitive_action
self.execution_stats: "NodeExecutionStats" = NodeExecutionStats()
if self.webhook_config:
if isinstance(self.webhook_config, BlockWebhookConfig):
# Enforce presence of credentials field on auto-setup webhook blocks
if not (cred_fields := self.input_schema.get_credentials_fields()):
raise TypeError(
"credentials field is required on auto-setup webhook blocks"
)
# Disallow multiple credentials inputs on webhook blocks
elif len(cred_fields) > 1:
raise ValueError(
"Multiple credentials inputs not supported on webhook blocks"
)
self.block_type = BlockType.WEBHOOK
else:
self.block_type = BlockType.WEBHOOK_MANUAL
# Enforce shape of webhook event filter, if present
if self.webhook_config.event_filter_input:
event_filter_field = self.input_schema.model_fields[
self.webhook_config.event_filter_input
]
if not (
isinstance(event_filter_field.annotation, type)
and issubclass(event_filter_field.annotation, BaseModel)
and all(
field.annotation is bool
for field in event_filter_field.annotation.model_fields.values()
)
):
raise NotImplementedError(
f"{self.name} has an invalid webhook event selector: "
"field must be a BaseModel and all its fields must be boolean"
)
# Enforce presence of 'payload' input
if "payload" not in self.input_schema.model_fields:
raise TypeError(
f"{self.name} is webhook-triggered but has no 'payload' input"
)
# Disable webhook-triggered block if webhook functionality not available
if not app_config.platform_base_url:
self.disabled = True
@abstractmethod
async def run(self, input_data: BlockSchemaInputType, **kwargs) -> BlockOutput:
"""
Run the block with the given input data.
Args:
input_data: The input data with the structure of input_schema.
Kwargs: Currently 14/02/2025 these include
graph_id: The ID of the graph.
node_id: The ID of the node.
graph_exec_id: The ID of the graph execution.
node_exec_id: The ID of the node execution.
user_id: The ID of the user.
Returns:
A Generator that yields (output_name, output_data).
output_name: One of the output name defined in Block's output_schema.
output_data: The data for the output_name, matching the defined schema.
"""
# --- satisfy the type checker, never executed -------------
if False: # noqa: SIM115
yield "name", "value" # pyright: ignore[reportMissingYield]
raise NotImplementedError(f"{self.name} does not implement the run method.")
async def run_once(
self, input_data: BlockSchemaInputType, output: str, **kwargs
) -> Any:
async for item in self.run(input_data, **kwargs):
name, data = item
if name == output:
return data
raise ValueError(f"{self.name} did not produce any output for {output}")
def merge_stats(self, stats: "NodeExecutionStats") -> "NodeExecutionStats":
self.execution_stats += stats
return self.execution_stats
@property
def name(self):
return self.__class__.__name__
def to_dict(self):
return {
"id": self.id,
"name": self.name,
"inputSchema": self.input_schema.jsonschema(),
"outputSchema": self.output_schema.jsonschema(),
"description": self.description,
"categories": [category.dict() for category in self.categories],
"contributors": [
contributor.model_dump() for contributor in self.contributors
],
"staticOutput": self.static_output,
"uiType": self.block_type.value,
}
def get_info(self) -> BlockInfo:
from backend.data.credit import get_block_cost
return BlockInfo(
id=self.id,
name=self.name,
inputSchema=self.input_schema.jsonschema(),
outputSchema=self.output_schema.jsonschema(),
costs=get_block_cost(self),
description=self.description,
categories=[category.dict() for category in self.categories],
contributors=[
contributor.model_dump() for contributor in self.contributors
],
staticOutput=self.static_output,
uiType=self.block_type.value,
)
async def execute(self, input_data: BlockInput, **kwargs) -> BlockOutput:
try:
async for output_name, output_data in self._execute(input_data, **kwargs):
yield output_name, output_data
except Exception as ex:
if isinstance(ex, BlockError):
raise ex
else:
raise (
BlockExecutionError
if isinstance(ex, ValueError)
else BlockUnknownError
)(
message=str(ex),
block_name=self.name,
block_id=self.id,
) from ex
async def is_block_exec_need_review(
self,
input_data: BlockInput,
*,
user_id: str,
node_id: str,
node_exec_id: str,
graph_exec_id: str,
graph_id: str,
graph_version: int,
execution_context: "ExecutionContext",
**kwargs,
) -> tuple[bool, BlockInput]:
"""
Check if this block execution needs human review and handle the review process.
Returns:
Tuple of (should_pause, input_data_to_use)
- should_pause: True if execution should be paused for review
- input_data_to_use: The input data to use (may be modified by reviewer)
"""
if not (
self.is_sensitive_action and execution_context.sensitive_action_safe_mode
):
return False, input_data
from backend.blocks.helpers.review import HITLReviewHelper
# Handle the review request and get decision
decision = await HITLReviewHelper.handle_review_decision(
input_data=input_data,
user_id=user_id,
node_id=node_id,
node_exec_id=node_exec_id,
graph_exec_id=graph_exec_id,
graph_id=graph_id,
graph_version=graph_version,
block_name=self.name,
editable=True,
)
if decision is None:
# We're awaiting review - pause execution
return True, input_data
if not decision.should_proceed:
# Review was rejected, raise an error to stop execution
raise BlockExecutionError(
message=f"Block execution rejected by reviewer: {decision.message}",
block_name=self.name,
block_id=self.id,
)
# Review was approved - use the potentially modified data
# ReviewResult.data must be a dict for block inputs
reviewed_data = decision.review_result.data
if not isinstance(reviewed_data, dict):
raise BlockExecutionError(
message=f"Review data must be a dict for block input, got {type(reviewed_data).__name__}",
block_name=self.name,
block_id=self.id,
)
return False, reviewed_data
async def _execute(self, input_data: BlockInput, **kwargs) -> BlockOutput:
# Check for review requirement only if running within a graph execution context
# Direct block execution (e.g., from chat) skips the review process
has_graph_context = all(
key in kwargs
for key in (
"node_exec_id",
"graph_exec_id",
"graph_id",
"execution_context",
)
)
if has_graph_context:
should_pause, input_data = await self.is_block_exec_need_review(
input_data, **kwargs
)
if should_pause:
return
# Validate the input data (original or reviewer-modified) once
if error := self.input_schema.validate_data(input_data):
raise BlockInputError(
message=f"Unable to execute block with invalid input data: {error}",
block_name=self.name,
block_id=self.id,
)
# Use the validated input data
async for output_name, output_data in self.run(
self.input_schema(**{k: v for k, v in input_data.items() if v is not None}),
**kwargs,
):
if output_name == "error":
raise BlockExecutionError(
message=output_data, block_name=self.name, block_id=self.id
)
if self.block_type == BlockType.STANDARD and (
error := self.output_schema.validate_field(output_name, output_data)
):
raise BlockOutputError(
message=f"Block produced an invalid output data: {error}",
block_name=self.name,
block_id=self.id,
)
yield output_name, output_data
def is_triggered_by_event_type(
self, trigger_config: dict[str, Any], event_type: str
) -> bool:
if not self.webhook_config:
raise TypeError("This method can't be used on non-trigger blocks")
if not self.webhook_config.event_filter_input:
return True
event_filter = trigger_config.get(self.webhook_config.event_filter_input)
if not event_filter:
raise ValueError("Event filter is not configured on trigger")
return event_type in [
self.webhook_config.event_format.format(event=k)
for k in event_filter
if event_filter[k] is True
]
# Type alias for any block with standard input/output schemas
AnyBlockSchema: TypeAlias = Block[BlockSchemaInput, BlockSchemaOutput]

View File

@@ -1,122 +0,0 @@
import logging
import os
from backend.integrations.providers import ProviderName
from ._base import AnyBlockSchema
logger = logging.getLogger(__name__)
def is_block_auth_configured(
block_cls: type[AnyBlockSchema],
) -> bool:
"""
Check if a block has a valid authentication method configured at runtime.
For example if a block is an OAuth-only block and there env vars are not set,
do not show it in the UI.
"""
from backend.sdk.registry import AutoRegistry
# Create an instance to access input_schema
try:
block = block_cls()
except Exception as e:
# If we can't create a block instance, assume it's not OAuth-only
logger.error(f"Error creating block instance for {block_cls.__name__}: {e}")
return True
logger.debug(
f"Checking if block {block_cls.__name__} has a valid provider configured"
)
# Get all credential inputs from input schema
credential_inputs = block.input_schema.get_credentials_fields_info()
required_inputs = block.input_schema.get_required_fields()
if not credential_inputs:
logger.debug(
f"Block {block_cls.__name__} has no credential inputs - Treating as valid"
)
return True
# Check credential inputs
if len(required_inputs.intersection(credential_inputs.keys())) == 0:
logger.debug(
f"Block {block_cls.__name__} has only optional credential inputs"
" - will work without credentials configured"
)
# Check if the credential inputs for this block are correctly configured
for field_name, field_info in credential_inputs.items():
provider_names = field_info.provider
if not provider_names:
logger.warning(
f"Block {block_cls.__name__} "
f"has credential input '{field_name}' with no provider options"
" - Disabling"
)
return False
# If a field has multiple possible providers, each one needs to be usable to
# prevent breaking the UX
for _provider_name in provider_names:
provider_name = _provider_name.value
if provider_name in ProviderName.__members__.values():
logger.debug(
f"Block {block_cls.__name__} credential input '{field_name}' "
f"provider '{provider_name}' is part of the legacy provider system"
" - Treating as valid"
)
break
provider = AutoRegistry.get_provider(provider_name)
if not provider:
logger.warning(
f"Block {block_cls.__name__} credential input '{field_name}' "
f"refers to unknown provider '{provider_name}' - Disabling"
)
return False
# Check the provider's supported auth types
if field_info.supported_types != provider.supported_auth_types:
logger.warning(
f"Block {block_cls.__name__} credential input '{field_name}' "
f"has mismatched supported auth types (field <> Provider): "
f"{field_info.supported_types} != {provider.supported_auth_types}"
)
if not (supported_auth_types := provider.supported_auth_types):
# No auth methods are been configured for this provider
logger.warning(
f"Block {block_cls.__name__} credential input '{field_name}' "
f"provider '{provider_name}' "
"has no authentication methods configured - Disabling"
)
return False
# Check if provider supports OAuth
if "oauth2" in supported_auth_types:
# Check if OAuth environment variables are set
if (oauth_config := provider.oauth_config) and bool(
os.getenv(oauth_config.client_id_env_var)
and os.getenv(oauth_config.client_secret_env_var)
):
logger.debug(
f"Block {block_cls.__name__} credential input '{field_name}' "
f"provider '{provider_name}' is configured for OAuth"
)
else:
logger.error(
f"Block {block_cls.__name__} credential input '{field_name}' "
f"provider '{provider_name}' "
"is missing OAuth client ID or secret - Disabling"
)
return False
logger.debug(
f"Block {block_cls.__name__} credential input '{field_name}' is valid; "
f"supported credential types: {', '.join(field_info.supported_types)}"
)
return True

View File

@@ -1,7 +1,7 @@
import logging
from typing import TYPE_CHECKING, Any, Optional
from typing import Any, Optional
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockInput,
@@ -9,15 +9,13 @@ from backend.blocks._base import (
BlockSchema,
BlockSchemaInput,
BlockType,
get_block,
)
from backend.data.execution import ExecutionContext, ExecutionStatus, NodesInputMasks
from backend.data.model import NodeExecutionStats, SchemaField
from backend.util.json import validate_with_jsonschema
from backend.util.retry import func_retry
if TYPE_CHECKING:
from backend.executor.utils import LogMetadata
_logger = logging.getLogger(__name__)
@@ -126,10 +124,9 @@ class AgentExecutorBlock(Block):
graph_version: int,
graph_exec_id: str,
user_id: str,
logger: "LogMetadata",
logger,
) -> BlockOutput:
from backend.blocks import get_block
from backend.data.execution import ExecutionEventType
from backend.executor import utils as execution_utils
@@ -201,7 +198,7 @@ class AgentExecutorBlock(Block):
self,
graph_exec_id: str,
user_id: str,
logger: "LogMetadata",
logger,
) -> None:
from backend.executor import utils as execution_utils

View File

@@ -1,11 +1,5 @@
from typing import Any
from backend.blocks._base import (
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.blocks.llm import (
DEFAULT_LLM_MODEL,
TEST_CREDENTIALS,
@@ -17,6 +11,12 @@ from backend.blocks.llm import (
LLMResponse,
llm_call,
)
from backend.data.block import (
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.data.model import APIKeyCredentials, NodeExecutionStats, SchemaField

View File

@@ -6,7 +6,7 @@ from pydantic import SecretStr
from replicate.client import Client as ReplicateClient
from replicate.helpers import FileOutput
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -5,12 +5,7 @@ from pydantic import SecretStr
from replicate.client import Client as ReplicateClient
from replicate.helpers import FileOutput
from backend.blocks._base import (
Block,
BlockCategory,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.data.block import Block, BlockCategory, BlockSchemaInput, BlockSchemaOutput
from backend.data.execution import ExecutionContext
from backend.data.model import (
APIKeyCredentials,

View File

@@ -6,7 +6,7 @@ from typing import Literal
from pydantic import SecretStr
from replicate.client import Client as ReplicateClient
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -6,7 +6,7 @@ from typing import Literal
from pydantic import SecretStr
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -1,10 +1,3 @@
from backend.blocks._base import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.blocks.apollo._api import ApolloClient
from backend.blocks.apollo._auth import (
TEST_CREDENTIALS,
@@ -17,6 +10,13 @@ from backend.blocks.apollo.models import (
PrimaryPhone,
SearchOrganizationsRequest,
)
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.data.model import CredentialsField, SchemaField

View File

@@ -1,12 +1,5 @@
import asyncio
from backend.blocks._base import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.blocks.apollo._api import ApolloClient
from backend.blocks.apollo._auth import (
TEST_CREDENTIALS,
@@ -21,6 +14,13 @@ from backend.blocks.apollo.models import (
SearchPeopleRequest,
SenorityLevels,
)
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.data.model import CredentialsField, SchemaField

View File

@@ -1,10 +1,3 @@
from backend.blocks._base import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.blocks.apollo._api import ApolloClient
from backend.blocks.apollo._auth import (
TEST_CREDENTIALS,
@@ -13,6 +6,13 @@ from backend.blocks.apollo._auth import (
ApolloCredentialsInput,
)
from backend.blocks.apollo.models import Contact, EnrichPersonRequest
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.data.model import CredentialsField, SchemaField

View File

@@ -3,7 +3,7 @@ from typing import Optional
from pydantic import BaseModel, Field
from backend.blocks._base import BlockSchemaInput
from backend.data.block import BlockSchemaInput
from backend.data.model import SchemaField, UserIntegrations
from backend.integrations.ayrshare import AyrshareClient
from backend.util.clients import get_database_manager_async_client

View File

@@ -1,7 +1,7 @@
import enum
from typing import Any
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -2,7 +2,7 @@ import os
import re
from typing import Type
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -1,7 +1,7 @@
from enum import Enum
from typing import Any
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -1,12 +1,12 @@
import json
import shlex
import uuid
from typing import TYPE_CHECKING, Literal, Optional
from typing import Literal, Optional
from e2b import AsyncSandbox as BaseAsyncSandbox
from pydantic import SecretStr
from pydantic import BaseModel, SecretStr
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
@@ -20,13 +20,6 @@ from backend.data.model import (
SchemaField,
)
from backend.integrations.providers import ProviderName
from backend.util.sandbox_files import (
SandboxFileOutput,
extract_and_store_sandbox_files,
)
if TYPE_CHECKING:
from backend.executor.utils import ExecutionContext
class ClaudeCodeExecutionError(Exception):
@@ -181,15 +174,22 @@ class ClaudeCodeBlock(Block):
advanced=True,
)
class FileOutput(BaseModel):
"""A file extracted from the sandbox."""
path: str
relative_path: str # Path relative to working directory (for GitHub, etc.)
name: str
content: str
class Output(BlockSchemaOutput):
response: str = SchemaField(
description="The output/response from Claude Code execution"
)
files: list[SandboxFileOutput] = SchemaField(
files: list["ClaudeCodeBlock.FileOutput"] = SchemaField(
description=(
"List of text files created/modified by Claude Code during this execution. "
"Each file has 'path', 'relative_path', 'name', 'content', and 'workspace_ref' fields. "
"workspace_ref contains a workspace:// URI if the file was stored to workspace."
"Each file has 'path', 'relative_path', 'name', and 'content' fields."
)
)
conversation_history: str = SchemaField(
@@ -252,7 +252,6 @@ class ClaudeCodeBlock(Block):
"relative_path": "index.html",
"name": "index.html",
"content": "<html>Hello World</html>",
"workspace_ref": None,
}
],
),
@@ -268,12 +267,11 @@ class ClaudeCodeBlock(Block):
"execute_claude_code": lambda *args, **kwargs: (
"Created index.html with hello world content", # response
[
SandboxFileOutput(
ClaudeCodeBlock.FileOutput(
path="/home/user/index.html",
relative_path="index.html",
name="index.html",
content="<html>Hello World</html>",
workspace_ref=None,
)
], # files
"User: Create a hello world HTML file\n"
@@ -296,8 +294,7 @@ class ClaudeCodeBlock(Block):
existing_sandbox_id: str,
conversation_history: str,
dispose_sandbox: bool,
execution_context: "ExecutionContext",
) -> tuple[str, list[SandboxFileOutput], str, str, str]:
) -> tuple[str, list["ClaudeCodeBlock.FileOutput"], str, str, str]:
"""
Execute Claude Code in an E2B sandbox.
@@ -452,18 +449,14 @@ class ClaudeCodeBlock(Block):
else:
new_conversation_history = turn_entry
# Extract files created/modified during this run and store to workspace
sandbox_files = await extract_and_store_sandbox_files(
sandbox=sandbox,
working_directory=working_directory,
execution_context=execution_context,
since_timestamp=start_timestamp,
text_only=True,
# Extract files created/modified during this run
files = await self._extract_files(
sandbox, working_directory, start_timestamp
)
return (
response,
sandbox_files, # Already SandboxFileOutput objects
files,
new_conversation_history,
current_session_id,
sandbox_id,
@@ -478,6 +471,140 @@ class ClaudeCodeBlock(Block):
if dispose_sandbox and sandbox:
await sandbox.kill()
async def _extract_files(
self,
sandbox: BaseAsyncSandbox,
working_directory: str,
since_timestamp: str | None = None,
) -> list["ClaudeCodeBlock.FileOutput"]:
"""
Extract text files created/modified during this Claude Code execution.
Args:
sandbox: The E2B sandbox instance
working_directory: Directory to search for files
since_timestamp: ISO timestamp - only return files modified after this time
Returns:
List of FileOutput objects with path, relative_path, name, and content
"""
files: list[ClaudeCodeBlock.FileOutput] = []
# Text file extensions we can safely read as text
text_extensions = {
".txt",
".md",
".html",
".htm",
".css",
".js",
".ts",
".jsx",
".tsx",
".json",
".xml",
".yaml",
".yml",
".toml",
".ini",
".cfg",
".conf",
".py",
".rb",
".php",
".java",
".c",
".cpp",
".h",
".hpp",
".cs",
".go",
".rs",
".swift",
".kt",
".scala",
".sh",
".bash",
".zsh",
".sql",
".graphql",
".env",
".gitignore",
".dockerfile",
"Dockerfile",
".vue",
".svelte",
".astro",
".mdx",
".rst",
".tex",
".csv",
".log",
}
try:
# List files recursively using find command
# Exclude node_modules and .git directories, but allow hidden files
# like .env and .gitignore (they're filtered by text_extensions later)
# Filter by timestamp to only get files created/modified during this run
safe_working_dir = shlex.quote(working_directory)
timestamp_filter = ""
if since_timestamp:
timestamp_filter = f"-newermt {shlex.quote(since_timestamp)} "
find_result = await sandbox.commands.run(
f"find {safe_working_dir} -type f "
f"{timestamp_filter}"
f"-not -path '*/node_modules/*' "
f"-not -path '*/.git/*' "
f"2>/dev/null"
)
if find_result.stdout:
for file_path in find_result.stdout.strip().split("\n"):
if not file_path:
continue
# Check if it's a text file we can read
is_text = any(
file_path.endswith(ext) for ext in text_extensions
) or file_path.endswith("Dockerfile")
if is_text:
try:
content = await sandbox.files.read(file_path)
# Handle bytes or string
if isinstance(content, bytes):
content = content.decode("utf-8", errors="replace")
# Extract filename from path
file_name = file_path.split("/")[-1]
# Calculate relative path by stripping working directory
relative_path = file_path
if file_path.startswith(working_directory):
relative_path = file_path[len(working_directory) :]
# Remove leading slash if present
if relative_path.startswith("/"):
relative_path = relative_path[1:]
files.append(
ClaudeCodeBlock.FileOutput(
path=file_path,
relative_path=relative_path,
name=file_name,
content=content,
)
)
except Exception:
# Skip files that can't be read
pass
except Exception:
# If file extraction fails, return empty results
pass
return files
def _escape_prompt(self, prompt: str) -> str:
"""Escape the prompt for safe shell execution."""
# Use single quotes and escape any single quotes in the prompt
@@ -490,7 +617,6 @@ class ClaudeCodeBlock(Block):
*,
e2b_credentials: APIKeyCredentials,
anthropic_credentials: APIKeyCredentials,
execution_context: "ExecutionContext",
**kwargs,
) -> BlockOutput:
try:
@@ -511,7 +637,6 @@ class ClaudeCodeBlock(Block):
existing_sandbox_id=input_data.sandbox_id,
conversation_history=input_data.conversation_history,
dispose_sandbox=input_data.dispose_sandbox,
execution_context=execution_context,
)
yield "response", response

View File

@@ -1,12 +1,12 @@
from enum import Enum
from typing import TYPE_CHECKING, Any, Literal, Optional
from typing import Any, Literal, Optional
from e2b_code_interpreter import AsyncSandbox
from e2b_code_interpreter import Result as E2BExecutionResult
from e2b_code_interpreter.charts import Chart as E2BExecutionResultChart
from pydantic import BaseModel, Field, JsonValue, SecretStr
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
@@ -20,13 +20,6 @@ from backend.data.model import (
SchemaField,
)
from backend.integrations.providers import ProviderName
from backend.util.sandbox_files import (
SandboxFileOutput,
extract_and_store_sandbox_files,
)
if TYPE_CHECKING:
from backend.executor.utils import ExecutionContext
TEST_CREDENTIALS = APIKeyCredentials(
id="01234567-89ab-cdef-0123-456789abcdef",
@@ -92,9 +85,6 @@ class CodeExecutionResult(MainCodeExecutionResult):
class BaseE2BExecutorMixin:
"""Shared implementation methods for E2B executor blocks."""
# Default working directory in E2B sandboxes
WORKING_DIR = "/home/user"
async def execute_code(
self,
api_key: str,
@@ -105,21 +95,14 @@ class BaseE2BExecutorMixin:
timeout: Optional[int] = None,
sandbox_id: Optional[str] = None,
dispose_sandbox: bool = False,
execution_context: Optional["ExecutionContext"] = None,
extract_files: bool = False,
):
"""
Unified code execution method that handles all three use cases:
1. Create new sandbox and execute (ExecuteCodeBlock)
2. Create new sandbox, execute, and return sandbox_id (InstantiateCodeSandboxBlock)
3. Connect to existing sandbox and execute (ExecuteCodeStepBlock)
Args:
extract_files: If True and execution_context provided, extract files
created/modified during execution and store to workspace.
""" # noqa
sandbox = None
files: list[SandboxFileOutput] = []
try:
if sandbox_id:
# Connect to existing sandbox (ExecuteCodeStepBlock case)
@@ -135,12 +118,6 @@ class BaseE2BExecutorMixin:
for cmd in setup_commands:
await sandbox.commands.run(cmd)
# Capture timestamp before execution to scope file extraction
start_timestamp = None
if extract_files:
ts_result = await sandbox.commands.run("date -u +%Y-%m-%dT%H:%M:%S")
start_timestamp = ts_result.stdout.strip() if ts_result.stdout else None
# Execute the code
execution = await sandbox.run_code(
code,
@@ -156,24 +133,7 @@ class BaseE2BExecutorMixin:
stdout_logs = "".join(execution.logs.stdout)
stderr_logs = "".join(execution.logs.stderr)
# Extract files created/modified during this execution
if extract_files and execution_context:
files = await extract_and_store_sandbox_files(
sandbox=sandbox,
working_directory=self.WORKING_DIR,
execution_context=execution_context,
since_timestamp=start_timestamp,
text_only=False, # Include binary files too
)
return (
results,
text_output,
stdout_logs,
stderr_logs,
sandbox.sandbox_id,
files,
)
return results, text_output, stdout_logs, stderr_logs, sandbox.sandbox_id
finally:
# Dispose of sandbox if requested to reduce usage costs
if dispose_sandbox and sandbox:
@@ -278,12 +238,6 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
description="Standard output logs from execution"
)
stderr_logs: str = SchemaField(description="Standard error logs from execution")
files: list[SandboxFileOutput] = SchemaField(
description=(
"Files created or modified during execution. "
"Each file has path, name, content, and workspace_ref (if stored)."
),
)
def __init__(self):
super().__init__(
@@ -305,30 +259,23 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
("results", []),
("response", "Hello World"),
("stdout_logs", "Hello World\n"),
("files", []),
],
test_mock={
"execute_code": lambda api_key, code, language, template_id, setup_commands, timeout, dispose_sandbox, execution_context, extract_files: ( # noqa
"execute_code": lambda api_key, code, language, template_id, setup_commands, timeout, dispose_sandbox: ( # noqa
[], # results
"Hello World", # text_output
"Hello World\n", # stdout_logs
"", # stderr_logs
"sandbox_id", # sandbox_id
[], # files
),
},
)
async def run(
self,
input_data: Input,
*,
credentials: APIKeyCredentials,
execution_context: "ExecutionContext",
**kwargs,
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
try:
results, text_output, stdout, stderr, _, files = await self.execute_code(
results, text_output, stdout, stderr, _ = await self.execute_code(
api_key=credentials.api_key.get_secret_value(),
code=input_data.code,
language=input_data.language,
@@ -336,8 +283,6 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
setup_commands=input_data.setup_commands,
timeout=input_data.timeout,
dispose_sandbox=input_data.dispose_sandbox,
execution_context=execution_context,
extract_files=True,
)
# Determine result object shape & filter out empty formats
@@ -351,8 +296,6 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
yield "stdout_logs", stdout
if stderr:
yield "stderr_logs", stderr
# Always yield files (empty list if none)
yield "files", [f.model_dump() for f in files]
except Exception as e:
yield "error", str(e)
@@ -450,7 +393,6 @@ class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
"Hello World\n", # stdout_logs
"", # stderr_logs
"sandbox_id", # sandbox_id
[], # files
),
},
)
@@ -459,7 +401,7 @@ class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
try:
_, text_output, stdout, stderr, sandbox_id, _ = await self.execute_code(
_, text_output, stdout, stderr, sandbox_id = await self.execute_code(
api_key=credentials.api_key.get_secret_value(),
code=input_data.setup_code,
language=input_data.language,
@@ -558,7 +500,6 @@ class ExecuteCodeStepBlock(Block, BaseE2BExecutorMixin):
"Hello World\n", # stdout_logs
"", # stderr_logs
sandbox_id, # sandbox_id
[], # files
),
},
)
@@ -567,7 +508,7 @@ class ExecuteCodeStepBlock(Block, BaseE2BExecutorMixin):
self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
) -> BlockOutput:
try:
results, text_output, stdout, stderr, _, _ = await self.execute_code(
results, text_output, stdout, stderr, _ = await self.execute_code(
api_key=credentials.api_key.get_secret_value(),
code=input_data.step_code,
language=input_data.language,

View File

@@ -1,6 +1,6 @@
import re
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -6,7 +6,7 @@ from openai import AsyncOpenAI
from openai.types.responses import Response as OpenAIResponse
from pydantic import SecretStr
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -1,6 +1,6 @@
from pydantic import BaseModel
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockManualWebhookConfig,

View File

@@ -1,4 +1,4 @@
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -1,6 +1,6 @@
from typing import Any, List
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -1,6 +1,6 @@
import codecs
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -8,7 +8,7 @@ from typing import Any, Literal, cast
import discord
from pydantic import SecretStr
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -2,7 +2,7 @@
Discord OAuth-based blocks.
"""
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -7,7 +7,7 @@ from typing import Literal
from pydantic import BaseModel, ConfigDict, SecretStr
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -2,7 +2,7 @@
import codecs
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -8,7 +8,7 @@ which provides access to LinkedIn profile data and related information.
import logging
from typing import Optional
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

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@@ -3,13 +3,6 @@ import logging
from enum import Enum
from typing import Any
from backend.blocks._base import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.blocks.fal._auth import (
TEST_CREDENTIALS,
TEST_CREDENTIALS_INPUT,
@@ -17,6 +10,13 @@ from backend.blocks.fal._auth import (
FalCredentialsField,
FalCredentialsInput,
)
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.data.execution import ExecutionContext
from backend.data.model import SchemaField
from backend.util.file import store_media_file

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@@ -5,7 +5,7 @@ from pydantic import SecretStr
from replicate.client import Client as ReplicateClient
from replicate.helpers import FileOutput
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

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@@ -3,7 +3,7 @@ from typing import Optional
from pydantic import BaseModel
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

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@@ -5,7 +5,7 @@ from typing import Optional
from typing_extensions import TypedDict
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

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@@ -3,7 +3,7 @@ from urllib.parse import urlparse
from typing_extensions import TypedDict
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

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@@ -2,7 +2,7 @@ import re
from typing_extensions import TypedDict
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

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@@ -2,7 +2,7 @@ import base64
from typing_extensions import TypedDict
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

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@@ -4,7 +4,7 @@ from typing import Any, List, Optional
from typing_extensions import TypedDict
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

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@@ -3,7 +3,7 @@ from typing import Optional
from pydantic import BaseModel
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -4,7 +4,7 @@ from pathlib import Path
from pydantic import BaseModel
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

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@@ -8,7 +8,7 @@ from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build
from pydantic import BaseModel
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -7,14 +7,14 @@ from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build
from gravitas_md2gdocs import to_requests
from backend.blocks._base import (
from backend.blocks.google._drive import GoogleDriveFile, GoogleDriveFileField
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.blocks.google._drive import GoogleDriveFile, GoogleDriveFileField
from backend.data.model import SchemaField
from backend.util.settings import Settings

View File

@@ -14,7 +14,7 @@ from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build
from pydantic import BaseModel, Field
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -7,14 +7,14 @@ from enum import Enum
from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build
from backend.blocks._base import (
from backend.blocks.google._drive import GoogleDriveFile, GoogleDriveFileField
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.blocks.google._drive import GoogleDriveFile, GoogleDriveFileField
from backend.data.model import SchemaField
from backend.util.settings import Settings

View File

@@ -3,7 +3,7 @@ from typing import Literal
import googlemaps
from pydantic import BaseModel, SecretStr
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -9,7 +9,9 @@ from typing import Any, Optional
from prisma.enums import ReviewStatus
from pydantic import BaseModel
from backend.data.execution import ExecutionStatus
from backend.data.human_review import ReviewResult
from backend.executor.manager import async_update_node_execution_status
from backend.util.clients import get_database_manager_async_client
logger = logging.getLogger(__name__)
@@ -41,8 +43,6 @@ class HITLReviewHelper:
@staticmethod
async def update_node_execution_status(**kwargs) -> None:
"""Update the execution status of a node."""
from backend.executor.manager import async_update_node_execution_status
await async_update_node_execution_status(
db_client=get_database_manager_async_client(), **kwargs
)
@@ -88,13 +88,12 @@ class HITLReviewHelper:
Raises:
Exception: If review creation or status update fails
"""
from backend.data.execution import ExecutionStatus
# Note: Safe mode checks (human_in_the_loop_safe_mode, sensitive_action_safe_mode)
# are handled by the caller:
# - HITL blocks check human_in_the_loop_safe_mode in their run() method
# - Sensitive action blocks check sensitive_action_safe_mode in is_block_exec_need_review()
# This function only handles checking for existing approvals.
# Check if this node has already been approved (normal or auto-approval)
if approval_result := await HITLReviewHelper.check_approval(
node_exec_id=node_exec_id,

View File

@@ -8,7 +8,7 @@ from typing import Literal
import aiofiles
from pydantic import SecretStr
from backend.blocks._base import (
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,

View File

@@ -1,15 +1,15 @@
from backend.blocks._base import (
from backend.blocks.hubspot._auth import (
HubSpotCredentials,
HubSpotCredentialsField,
HubSpotCredentialsInput,
)
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.blocks.hubspot._auth import (
HubSpotCredentials,
HubSpotCredentialsField,
HubSpotCredentialsInput,
)
from backend.data.model import SchemaField
from backend.util.request import Requests

View File

@@ -1,15 +1,15 @@
from backend.blocks._base import (
from backend.blocks.hubspot._auth import (
HubSpotCredentials,
HubSpotCredentialsField,
HubSpotCredentialsInput,
)
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.blocks.hubspot._auth import (
HubSpotCredentials,
HubSpotCredentialsField,
HubSpotCredentialsInput,
)
from backend.data.model import SchemaField
from backend.util.request import Requests

View File

@@ -1,17 +1,17 @@
from datetime import datetime, timedelta
from backend.blocks._base import (
from backend.blocks.hubspot._auth import (
HubSpotCredentials,
HubSpotCredentialsField,
HubSpotCredentialsInput,
)
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.blocks.hubspot._auth import (
HubSpotCredentials,
HubSpotCredentialsField,
HubSpotCredentialsInput,
)
from backend.data.model import SchemaField
from backend.util.request import Requests

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