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6 Commits

Author SHA1 Message Date
Zamil Majdy
4eac081cf9 feat(frontend): update OpenAPI schema for is_ai_generated fields
- Add is_ai_generated field to CreateGraph model
- Add is_ai_generated_graph field to GraphSettings model
- Sync frontend API schema with backend changes
2026-01-12 16:30:34 -06:00
Zamil Majdy
eef7cf8cf8 fix(backend): preserve is_ai_generated_graph on fork and make parameter mandatory
- Fix bug where forking a library agent would reset is_ai_generated_graph to False
  - Now preserves the original agent's is_ai_generated_graph flag
  - Ensures forked AI-generated agents maintain safety requirements

- Make is_ai_generated parameter mandatory in create_library_agent()
  - Moved parameter before optional parameters for consistency
  - Removed default value to force explicit decisions at all call sites
  - Updated all 4 call sites to explicitly pass the parameter

- Update snapshot test for new is_ai_generated_graph field in settings

All 33 tests passing
2026-01-12 16:12:10 -06:00
Zamil Majdy
7c90b16209 Merge branch 'dev' into feat/ai-generated-mode 2026-01-12 15:41:14 -06:00
Zamil Majdy
3ec2f1953f refactor(backend): make is_ai_generated parameter mandatory in GraphSettings.from_graph()
- Removed default value from is_ai_generated parameter
- Forces all callers to explicitly specify whether graph is AI-generated
- Explicitly set is_ai_generated=False for store installations (curated user-published agents)
- Makes the code more explicit and prevents accidental defaults
2026-01-12 15:35:24 -06:00
Zamil Majdy
8d3dfe2cf8 fix(backend): preserve is_ai_generated_graph flag on version update
When updating a library agent to a new version, the is_ai_generated_graph
flag was being reset to False (the default), disabling human review for
AI-generated graphs on subsequent runs.

Fix: Pass the existing is_ai_generated_graph value from library.settings
to GraphSettings.from_graph() to preserve the flag across version updates.

Uses from_graph() to reduce duplication while preserving all settings.
2026-01-12 15:22:13 -06:00
Zamil Majdy
7133580d43 feat(backend): add is_ai_generated_graph setting and cleanup human_in_the_loop_safe_mode duplication
- Add is_ai_generated_graph field to GraphSettings with default false
- Add GraphSettings.from_graph() class method for initialization
- Add is_ai_generated_graph to ExecutionContext
- Update block review logic: required_human_review blocks only pause for review if safe_mode=True AND is_ai_generated_graph=True
- HITL blocks continue to respect only safe_mode (unchanged)
- Expose is_ai_generated in CreateGraph API model and create_new_graph endpoint

Cleanup:
- Remove redundant update_library_agent_settings wrapper function (25 lines)
- Inline human_in_the_loop_safe_mode initialization logic using GraphSettings.from_graph()
- Remove unnecessary branching and comments
- Total: 68 lines removed, 34 lines added

Tests: All 33 tests passing (26 API + 7 executor)
2026-01-12 15:12:41 -06:00
13 changed files with 67 additions and 691 deletions

View File

@@ -166,6 +166,7 @@ async def get_or_create_library_agent(
library_agents = await library_db.create_library_agent(
graph=graph,
user_id=user_id,
is_ai_generated=False,
create_library_agents_for_sub_graphs=False,
)
assert len(library_agents) == 1, "Expected 1 library agent to be created"

View File

@@ -401,27 +401,10 @@ async def add_generated_agent_image(
)
def _initialize_graph_settings(graph: graph_db.GraphModel) -> GraphSettings:
"""
Initialize GraphSettings based on graph content.
Args:
graph: The graph to analyze
Returns:
GraphSettings with appropriate human_in_the_loop_safe_mode value
"""
if graph.has_human_in_the_loop:
# Graph has HITL blocks - set safe mode to True by default
return GraphSettings(human_in_the_loop_safe_mode=True)
else:
# Graph has no HITL blocks - keep None
return GraphSettings(human_in_the_loop_safe_mode=None)
async def create_library_agent(
graph: graph_db.GraphModel,
user_id: str,
is_ai_generated: bool,
create_library_agents_for_sub_graphs: bool = True,
) -> list[library_model.LibraryAgent]:
"""
@@ -431,6 +414,7 @@ async def create_library_agent(
agent: The agent/Graph to add to the library.
user_id: The user to whom the agent will be added.
create_library_agents_for_sub_graphs: If True, creates LibraryAgent records for sub-graphs as well.
is_ai_generated: Whether this graph was AI-generated.
Returns:
The newly created LibraryAgent records.
@@ -465,7 +449,9 @@ async def create_library_agent(
}
},
settings=SafeJson(
_initialize_graph_settings(graph_entry).model_dump()
GraphSettings.from_graph(
graph_entry, is_ai_generated=is_ai_generated
).model_dump()
),
),
include=library_agent_include(
@@ -627,33 +613,6 @@ async def update_library_agent(
raise DatabaseError("Failed to update library agent") from e
async def update_library_agent_settings(
user_id: str,
agent_id: str,
settings: GraphSettings,
) -> library_model.LibraryAgent:
"""
Updates the settings for a specific LibraryAgent.
Args:
user_id: The owner of the LibraryAgent.
agent_id: The ID of the LibraryAgent to update.
settings: New GraphSettings to apply.
Returns:
The updated LibraryAgent.
Raises:
NotFoundError: If the specified LibraryAgent does not exist.
DatabaseError: If there's an error in the update operation.
"""
return await update_library_agent(
library_agent_id=agent_id,
user_id=user_id,
settings=settings,
)
async def delete_library_agent(
library_agent_id: str, user_id: str, soft_delete: bool = True
) -> None:
@@ -838,7 +797,9 @@ async def add_store_agent_to_library(
"isCreatedByUser": False,
"useGraphIsActiveVersion": False,
"settings": SafeJson(
_initialize_graph_settings(graph_model).model_dump()
GraphSettings.from_graph(
graph_model, is_ai_generated=False
).model_dump()
),
},
include=library_agent_include(
@@ -1228,8 +1189,14 @@ async def fork_library_agent(
)
new_graph = await on_graph_activate(new_graph, user_id=user_id)
# Create a library agent for the new graph
return (await create_library_agent(new_graph, user_id))[0]
# Create a library agent for the new graph, preserving is_ai_generated flag
return (
await create_library_agent(
new_graph,
user_id,
is_ai_generated=original_agent.settings.is_ai_generated_graph,
)
)[0]
except prisma.errors.PrismaError as e:
logger.error(f"Database error cloning library agent: {e}")
raise DatabaseError("Failed to fork library agent") from e

View File

@@ -762,10 +762,10 @@ async def create_new_graph(
graph.reassign_ids(user_id=user_id, reassign_graph_id=True)
graph.validate_graph(for_run=False)
# The return value of the create graph & library function is intentionally not used here,
# as the graph already valid and no sub-graphs are returned back.
await graph_db.create_graph(graph, user_id=user_id)
await library_db.create_library_agent(graph, user_id=user_id)
await library_db.create_library_agent(
graph, user_id, is_ai_generated=create_graph.is_ai_generated
)
activated_graph = await on_graph_activate(graph, user_id=user_id)
if create_graph.source == "builder":
@@ -889,21 +889,17 @@ async def set_graph_active_version(
async def _update_library_agent_version_and_settings(
user_id: str, agent_graph: graph_db.GraphModel
) -> library_model.LibraryAgent:
# Keep the library agent up to date with the new active version
library = await library_db.update_agent_version_in_library(
user_id, agent_graph.id, agent_graph.version
)
# If the graph has HITL node, initialize the setting if it's not already set.
if (
agent_graph.has_human_in_the_loop
and library.settings.human_in_the_loop_safe_mode is None
):
await library_db.update_library_agent_settings(
updated_settings = GraphSettings.from_graph(
agent_graph, is_ai_generated=library.settings.is_ai_generated_graph
)
if updated_settings != library.settings:
library = await library_db.update_library_agent(
library_agent_id=library.id,
user_id=user_id,
agent_id=library.id,
settings=library.settings.model_copy(
update={"human_in_the_loop_safe_mode": True}
),
settings=updated_settings,
)
return library
@@ -920,21 +916,18 @@ async def update_graph_settings(
user_id: Annotated[str, Security(get_user_id)],
) -> GraphSettings:
"""Update graph settings for the user's library agent."""
# Get the library agent for this graph
library_agent = await library_db.get_library_agent_by_graph_id(
graph_id=graph_id, user_id=user_id
)
if not library_agent:
raise HTTPException(404, f"Graph #{graph_id} not found in user's library")
# Update the library agent settings
updated_agent = await library_db.update_library_agent_settings(
updated_agent = await library_db.update_library_agent(
library_agent_id=library_agent.id,
user_id=user_id,
agent_id=library_agent.id,
settings=settings,
)
# Return the updated settings
return GraphSettings.model_validate(updated_agent.settings)

View File

@@ -43,6 +43,7 @@ GraphExecutionSource = Literal["builder", "library", "onboarding"]
class CreateGraph(pydantic.BaseModel):
graph: Graph
source: GraphCreationSource | None = None
is_ai_generated: bool = False
class CreateAPIKeyRequest(pydantic.BaseModel):

View File

@@ -1,602 +0,0 @@
import shlex
from typing import Literal
from e2b import AsyncSandbox as BaseAsyncSandbox
from pydantic import BaseModel, SecretStr
from backend.data.block import (
Block,
BlockCategory,
BlockOutput,
BlockSchemaInput,
BlockSchemaOutput,
)
from backend.data.model import (
APIKeyCredentials,
CredentialsField,
CredentialsMetaInput,
SchemaField,
)
from backend.integrations.providers import ProviderName
# Test credentials for E2B
TEST_E2B_CREDENTIALS = APIKeyCredentials(
id="01234567-89ab-cdef-0123-456789abcdef",
provider="e2b",
api_key=SecretStr("mock-e2b-api-key"),
title="Mock E2B API key",
expires_at=None,
)
TEST_E2B_CREDENTIALS_INPUT = {
"provider": TEST_E2B_CREDENTIALS.provider,
"id": TEST_E2B_CREDENTIALS.id,
"type": TEST_E2B_CREDENTIALS.type,
"title": TEST_E2B_CREDENTIALS.title,
}
# Test credentials for Anthropic
TEST_ANTHROPIC_CREDENTIALS = APIKeyCredentials(
id="2e568a2b-b2ea-475a-8564-9a676bf31c56",
provider="anthropic",
api_key=SecretStr("mock-anthropic-api-key"),
title="Mock Anthropic API key",
expires_at=None,
)
TEST_ANTHROPIC_CREDENTIALS_INPUT = {
"provider": TEST_ANTHROPIC_CREDENTIALS.provider,
"id": TEST_ANTHROPIC_CREDENTIALS.id,
"type": TEST_ANTHROPIC_CREDENTIALS.type,
"title": TEST_ANTHROPIC_CREDENTIALS.title,
}
class ClaudeCodeBlock(Block):
"""
Execute tasks using Claude Code (Anthropic's AI coding assistant) in an E2B sandbox.
Claude Code can create files, install tools, run commands, and perform complex
coding tasks autonomously within a secure sandbox environment.
"""
# Use base template - we'll install Claude Code ourselves for latest version
DEFAULT_TEMPLATE = "base"
class Input(BlockSchemaInput):
e2b_credentials: CredentialsMetaInput[
Literal[ProviderName.E2B], Literal["api_key"]
] = CredentialsField(
description=(
"API key for the E2B platform to create the sandbox. "
"Get one at https://e2b.dev/docs"
),
)
anthropic_credentials: CredentialsMetaInput[
Literal[ProviderName.ANTHROPIC], Literal["api_key"]
] = CredentialsField(
description=(
"API key for Anthropic to power Claude Code. "
"Get one at https://console.anthropic.com/"
),
)
prompt: str = SchemaField(
description=(
"The task or instruction for Claude Code to execute. "
"Claude Code can create files, install packages, run commands, "
"and perform complex coding tasks."
),
placeholder="Create a hello world index.html file",
default="",
advanced=False,
)
timeout: int = SchemaField(
description=(
"Sandbox timeout in seconds. Claude Code tasks can take "
"a while, so set this appropriately for your task complexity. "
"Note: This only applies when creating a new sandbox. "
"When reconnecting to an existing sandbox via sandbox_id, "
"the original timeout is retained."
),
default=300, # 5 minutes default
advanced=True,
)
setup_commands: list[str] = SchemaField(
description=(
"Optional shell commands to run before executing Claude Code. "
"Useful for installing dependencies or setting up the environment."
),
default_factory=list,
advanced=True,
)
working_directory: str = SchemaField(
description="Working directory for Claude Code to operate in.",
default="/home/user",
advanced=True,
)
# Session/continuation support
session_id: str = SchemaField(
description=(
"Session ID to resume a previous conversation. "
"Leave empty for a new conversation. "
"Use the session_id from a previous run to continue that conversation."
),
default="",
advanced=True,
)
sandbox_id: str = SchemaField(
description=(
"Sandbox ID to reconnect to an existing sandbox. "
"Required when resuming a session (along with session_id). "
"Use the sandbox_id from a previous run where dispose_sandbox was False."
),
default="",
advanced=True,
)
conversation_history: str = SchemaField(
description=(
"Previous conversation history to continue from. "
"Use this to restore context on a fresh sandbox if the previous one timed out. "
"Pass the conversation_history output from a previous run."
),
default="",
advanced=True,
)
dispose_sandbox: bool = SchemaField(
description=(
"Whether to dispose of the sandbox immediately after execution. "
"Set to False if you want to continue the conversation later "
"(you'll need both sandbox_id and session_id from the output)."
),
default=True,
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["ClaudeCodeBlock.FileOutput"] = SchemaField(
description=(
"List of files created/modified by Claude Code. "
"Each file has 'path', 'name', and 'content' fields."
)
)
conversation_history: str = SchemaField(
description=(
"Full conversation history including this turn. "
"Pass this to conversation_history input to continue on a fresh sandbox "
"if the previous sandbox timed out."
)
)
session_id: str = SchemaField(
description=(
"Session ID for this conversation. "
"Pass this back along with sandbox_id to continue the conversation."
)
)
sandbox_id: str = SchemaField(
description=(
"ID of the sandbox instance. "
"Pass this back along with session_id to continue the conversation "
"(only available if dispose_sandbox was False)."
)
)
def __init__(self):
super().__init__(
id="4e34f4a5-9b89-4326-ba77-2dd6750b7194",
description=(
"Execute tasks using Claude Code in an E2B sandbox. "
"Claude Code can create files, install tools, run commands, "
"and perform complex coding tasks autonomously."
),
categories={BlockCategory.DEVELOPER_TOOLS, BlockCategory.AI},
input_schema=ClaudeCodeBlock.Input,
output_schema=ClaudeCodeBlock.Output,
test_credentials={
"e2b_credentials": TEST_E2B_CREDENTIALS,
"anthropic_credentials": TEST_ANTHROPIC_CREDENTIALS,
},
test_input={
"e2b_credentials": TEST_E2B_CREDENTIALS_INPUT,
"anthropic_credentials": TEST_ANTHROPIC_CREDENTIALS_INPUT,
"prompt": "Create a hello world HTML file",
"timeout": 300,
"setup_commands": [],
"working_directory": "/home/user",
"session_id": "",
"sandbox_id": "",
"conversation_history": "",
"dispose_sandbox": True,
},
test_output=[
("response", "Created index.html with hello world content"),
(
"files",
[
{
"path": "/home/user/index.html",
"relative_path": "index.html",
"name": "index.html",
"content": "<html>Hello World</html>",
}
],
),
(
"conversation_history",
"User: Create a hello world HTML file\n"
"Claude: Created index.html with hello world content",
),
("session_id", str),
],
test_mock={
"execute_claude_code": lambda *args, **kwargs: (
"Created index.html with hello world content", # response
[
ClaudeCodeBlock.FileOutput(
path="/home/user/index.html",
relative_path="index.html",
name="index.html",
content="<html>Hello World</html>",
)
], # files
"User: Create a hello world HTML file\n"
"Claude: Created index.html with hello world content", # conversation_history
"test-session-id", # session_id
"sandbox_id", # sandbox_id
),
},
)
async def execute_claude_code(
self,
e2b_api_key: str,
anthropic_api_key: str,
prompt: str,
timeout: int,
setup_commands: list[str],
working_directory: str,
session_id: str,
existing_sandbox_id: str,
conversation_history: str,
dispose_sandbox: bool,
) -> tuple[str, list["ClaudeCodeBlock.FileOutput"], str, str, str]:
"""
Execute Claude Code in an E2B sandbox.
Returns:
Tuple of (response, files, conversation_history, session_id, sandbox_id)
"""
import json
import uuid
# Validate that sandbox_id is provided when resuming a session
if session_id and not existing_sandbox_id:
raise ValueError(
"sandbox_id is required when resuming a session with session_id. "
"The session state is stored in the original sandbox. "
"If the sandbox has timed out, use conversation_history instead "
"to restore context on a fresh sandbox."
)
sandbox = None
try:
# Either reconnect to existing sandbox or create a new one
if existing_sandbox_id:
# Reconnect to existing sandbox for conversation continuation
sandbox = await BaseAsyncSandbox.connect(
sandbox_id=existing_sandbox_id,
api_key=e2b_api_key,
)
else:
# Create new sandbox
sandbox = await BaseAsyncSandbox.create(
template=self.DEFAULT_TEMPLATE,
api_key=e2b_api_key,
timeout=timeout,
envs={"ANTHROPIC_API_KEY": anthropic_api_key},
)
# Install Claude Code from npm (ensures we get the latest version)
install_result = await sandbox.commands.run(
"npm install -g @anthropic-ai/claude-code@latest",
timeout=120, # 2 min timeout for install
)
if install_result.exit_code != 0:
raise Exception(
f"Failed to install Claude Code: {install_result.stderr}"
)
# Run any user-provided setup commands
for cmd in setup_commands:
setup_result = await sandbox.commands.run(cmd)
if setup_result.exit_code != 0:
raise Exception(
f"Setup command failed: {cmd}\n"
f"Exit code: {setup_result.exit_code}\n"
f"Stdout: {setup_result.stdout}\n"
f"Stderr: {setup_result.stderr}"
)
# Generate or use provided session ID
current_session_id = session_id if session_id else str(uuid.uuid4())
# Build base Claude flags
base_flags = "-p --dangerously-skip-permissions --output-format json"
# Add conversation history context if provided (for fresh sandbox continuation)
history_flag = ""
if conversation_history and not session_id:
# Inject previous conversation as context via system prompt
# Use consistent escaping via _escape_prompt helper
escaped_history = self._escape_prompt(
f"Previous conversation context: {conversation_history}"
)
history_flag = f" --append-system-prompt {escaped_history}"
# Build Claude command based on whether we're resuming or starting new
# Use shlex.quote for working_directory and session IDs to prevent injection
safe_working_dir = shlex.quote(working_directory)
if session_id:
# Resuming existing session (sandbox still alive)
safe_session_id = shlex.quote(session_id)
claude_command = (
f"cd {safe_working_dir} && "
f"echo {self._escape_prompt(prompt)} | "
f"claude --resume {safe_session_id} {base_flags}"
)
else:
# New session with specific ID
safe_current_session_id = shlex.quote(current_session_id)
claude_command = (
f"cd {safe_working_dir} && "
f"echo {self._escape_prompt(prompt)} | "
f"claude --session-id {safe_current_session_id} {base_flags}{history_flag}"
)
result = await sandbox.commands.run(
claude_command,
timeout=0, # No command timeout - let sandbox timeout handle it
)
# Check for command failure
if result.exit_code != 0:
error_msg = result.stderr or result.stdout or "Unknown error"
raise Exception(
f"Claude Code command failed with exit code {result.exit_code}:\n"
f"{error_msg}"
)
raw_output = result.stdout or ""
sandbox_id = sandbox.sandbox_id
# Parse JSON output to extract response and build conversation history
response = ""
new_conversation_history = conversation_history or ""
try:
# The JSON output contains the result
output_data = json.loads(raw_output)
response = output_data.get("result", raw_output)
# Build conversation history entry
turn_entry = f"User: {prompt}\nClaude: {response}"
if new_conversation_history:
new_conversation_history = (
f"{new_conversation_history}\n\n{turn_entry}"
)
else:
new_conversation_history = turn_entry
except json.JSONDecodeError:
# If not valid JSON, use raw output
response = raw_output
turn_entry = f"User: {prompt}\nClaude: {response}"
if new_conversation_history:
new_conversation_history = (
f"{new_conversation_history}\n\n{turn_entry}"
)
else:
new_conversation_history = turn_entry
# Extract files from the working directory
files = await self._extract_files(sandbox, working_directory)
return (
response,
files,
new_conversation_history,
current_session_id,
sandbox_id,
)
finally:
if dispose_sandbox and sandbox:
await sandbox.kill()
async def _extract_files(
self,
sandbox: BaseAsyncSandbox,
working_directory: str,
) -> list["ClaudeCodeBlock.FileOutput"]:
"""
Extract files from the sandbox working directory.
Returns:
List of FileOutput objects with path, name, and content
"""
files: list[ClaudeCodeBlock.FileOutput] = []
# Text file extensions we can safely read
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)
safe_working_dir = shlex.quote(working_directory)
find_result = await sandbox.commands.run(
f"find {safe_working_dir} -type f "
f"-not -path '*/node_modules/*' "
f"-not -path '*/.git/*' "
f"2>/dev/null | head -100"
)
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
escaped = prompt.replace("'", "'\"'\"'")
return f"'{escaped}'"
async def run(
self,
input_data: Input,
*,
e2b_credentials: APIKeyCredentials,
anthropic_credentials: APIKeyCredentials,
**kwargs,
) -> BlockOutput:
try:
(
response,
files,
conversation_history,
session_id,
sandbox_id,
) = await self.execute_claude_code(
e2b_api_key=e2b_credentials.api_key.get_secret_value(),
anthropic_api_key=anthropic_credentials.api_key.get_secret_value(),
prompt=input_data.prompt,
timeout=input_data.timeout,
setup_commands=input_data.setup_commands,
working_directory=input_data.working_directory,
session_id=input_data.session_id,
existing_sandbox_id=input_data.sandbox_id,
conversation_history=input_data.conversation_history,
dispose_sandbox=input_data.dispose_sandbox,
)
yield "response", response
# Always yield files (empty list if none) to match Output schema
yield "files", [f.model_dump() for f in files]
# Always yield conversation_history so user can restore context on fresh sandbox
yield "conversation_history", conversation_history
# Always yield session_id so user can continue conversation
yield "session_id", session_id
if not input_data.dispose_sandbox and sandbox_id:
yield "sandbox_id", sandbox_id
except Exception as e:
yield "error", str(e)

View File

@@ -18,7 +18,6 @@ from backend.data.model import (
SchemaField,
)
from backend.integrations.providers import ProviderName
from backend.util.request import DEFAULT_USER_AGENT
class GetWikipediaSummaryBlock(Block, GetRequest):
@@ -40,27 +39,17 @@ class GetWikipediaSummaryBlock(Block, GetRequest):
output_schema=GetWikipediaSummaryBlock.Output,
test_input={"topic": "Artificial Intelligence"},
test_output=("summary", "summary content"),
test_mock={
"get_request": lambda url, headers, json: {"extract": "summary content"}
},
test_mock={"get_request": lambda url, json: {"extract": "summary content"}},
)
async def run(self, input_data: Input, **kwargs) -> BlockOutput:
topic = input_data.topic
# URL-encode the topic to handle spaces and special characters
encoded_topic = quote(topic, safe="")
url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{encoded_topic}"
# Set headers per Wikimedia robot policy (https://w.wiki/4wJS)
# - User-Agent: Required, must identify the bot
# - Accept-Encoding: gzip recommended to reduce bandwidth
headers = {
"User-Agent": DEFAULT_USER_AGENT,
"Accept-Encoding": "gzip, deflate",
}
url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{topic}"
# Note: User-Agent is now automatically set by the request library
# to comply with Wikimedia's robot policy (https://w.wiki/4wJS)
try:
response = await self.get_request(url, headers=headers, json=True)
response = await self.get_request(url, json=True)
if "extract" not in response:
raise ValueError(f"Unable to parse Wikipedia response: {response}")
yield "summary", response["extract"]

View File

@@ -637,8 +637,11 @@ class Block(ABC, Generic[BlockSchemaInputType, BlockSchemaOutputType]):
- should_pause: True if execution should be paused for review
- input_data_to_use: The input data to use (may be modified by reviewer)
"""
# Skip review if not required or safe mode is disabled
if not self.requires_human_review or not execution_context.safe_mode:
if not (
self.requires_human_review
and execution_context.safe_mode
and execution_context.is_ai_generated_graph
):
return False, input_data
from backend.blocks.helpers.review import HITLReviewHelper

View File

@@ -82,6 +82,7 @@ class ExecutionContext(BaseModel):
"""
safe_mode: bool = True
is_ai_generated_graph: bool = False
user_timezone: str = "UTC"
root_execution_id: Optional[str] = None
parent_execution_id: Optional[str] = None

View File

@@ -63,6 +63,14 @@ logger = logging.getLogger(__name__)
class GraphSettings(BaseModel):
human_in_the_loop_safe_mode: bool | None = None
is_ai_generated_graph: bool = False
@classmethod
def from_graph(cls, graph: "GraphModel", is_ai_generated: bool) -> "GraphSettings":
return cls(
human_in_the_loop_safe_mode=(True if graph.has_human_in_the_loop else None),
is_ai_generated_graph=is_ai_generated,
)
class Link(BaseDbModel):

View File

@@ -877,6 +877,7 @@ async def add_graph_execution(
if settings.human_in_the_loop_safe_mode is not None
else True
),
is_ai_generated_graph=settings.is_ai_generated_graph,
user_timezone=(
user.timezone if user.timezone != USER_TIMEZONE_NOT_SET else "UTC"
),

View File

@@ -34,7 +34,8 @@
"is_favorite": false,
"recommended_schedule_cron": null,
"settings": {
"human_in_the_loop_safe_mode": null
"human_in_the_loop_safe_mode": null,
"is_ai_generated_graph": false
},
"marketplace_listing": null
},
@@ -72,7 +73,8 @@
"is_favorite": false,
"recommended_schedule_cron": null,
"settings": {
"human_in_the_loop_safe_mode": null
"human_in_the_loop_safe_mode": null,
"is_ai_generated_graph": false
},
"marketplace_listing": null
}

View File

@@ -412,7 +412,9 @@ class TestDataCreator:
# Use the API function to create library agent
library_agents.extend(
v.model_dump()
for v in await create_library_agent(graph, user["id"])
for v in await create_library_agent(
graph, user["id"], is_ai_generated=False
)
)
except Exception as e:
print(f"Error creating library agent: {e}")

View File

@@ -6613,6 +6613,11 @@
{ "type": "null" }
],
"title": "Source"
},
"is_ai_generated": {
"type": "boolean",
"title": "Is Ai Generated",
"default": false
}
},
"type": "object",
@@ -7558,6 +7563,11 @@
"human_in_the_loop_safe_mode": {
"anyOf": [{ "type": "boolean" }, { "type": "null" }],
"title": "Human In The Loop Safe Mode"
},
"is_ai_generated_graph": {
"type": "boolean",
"title": "Is Ai Generated Graph",
"default": false
}
},
"type": "object",