Files
DocsGPT/application/api/user/base.py
Siddhant Rai 8ef321d784 feat: agent workflow builder (#2264)
* feat: implement WorkflowAgent and GraphExecutor for workflow management and execution

* refactor: workflow schemas and introduce WorkflowEngine

- Updated schemas in `schemas.py` to include new agent types and configurations.
- Created `WorkflowEngine` class in `workflow_engine.py` to manage workflow execution.
- Enhanced `StreamProcessor` to handle workflow-related data.
- Added new routes and utilities for managing workflows in the user API.
- Implemented validation and serialization functions for workflows.
- Established MongoDB collections and indexes for workflows and related entities.

* refactor: improve WorkflowAgent documentation and update type hints in WorkflowEngine

* feat: workflow builder and managing in frontend

- Added new endpoints for workflows in `endpoints.ts`.
- Implemented `getWorkflow`, `createWorkflow`, and `updateWorkflow` methods in `userService.ts`.
- Introduced new UI components for alerts, buttons, commands, dialogs, multi-select, popovers, and selects.
- Enhanced styling in `index.css` with new theme variables and animations.
- Refactored modal components for better layout and styling.
- Configured TypeScript paths and Vite aliases for cleaner imports.

* feat: add workflow preview component and related state management

- Implemented WorkflowPreview component for displaying workflow execution.
- Created WorkflowPreviewSlice for managing workflow preview state, including queries and execution steps.
- Added WorkflowMiniMap for visual representation of workflow nodes and their statuses.
- Integrated conversation handling with the ability to fetch answers and manage query states.
- Introduced reusable Sheet component for UI overlays.
- Updated Redux store to include workflowPreview reducer.

* feat: enhance workflow execution details and state management in WorkflowEngine and WorkflowPreview

* feat: enhance workflow components with improved UI and functionality

- Updated WorkflowPreview to allow text truncation for better display of long names.
- Enhanced BaseNode with connectable handles and improved styling for better visibility.
- Added MobileBlocker component to inform users about desktop requirements for the Workflow Builder.
- Introduced PromptTextArea component for improved variable insertion and search functionality, including upstream variable extraction and context addition.

* feat(workflow): add owner validation and graph version support

* fix: ruff lint

---------

Co-authored-by: Alex <a@tushynski.me>
2026-02-11 14:15:24 +00:00

247 lines
7.2 KiB
Python

"""
Shared utilities, database connections, and helper functions for user API routes.
"""
import datetime
import os
import uuid
from functools import wraps
from typing import Optional, Tuple
from bson.objectid import ObjectId
from flask import current_app, jsonify, make_response, Response
from pymongo import ReturnDocument
from werkzeug.utils import secure_filename
from application.core.mongo_db import MongoDB
from application.core.settings import settings
from application.storage.storage_creator import StorageCreator
from application.vectorstore.vector_creator import VectorCreator
storage = StorageCreator.get_storage()
mongo = MongoDB.get_client()
db = mongo[settings.MONGO_DB_NAME]
conversations_collection = db["conversations"]
sources_collection = db["sources"]
prompts_collection = db["prompts"]
feedback_collection = db["feedback"]
agents_collection = db["agents"]
agent_folders_collection = db["agent_folders"]
token_usage_collection = db["token_usage"]
shared_conversations_collections = db["shared_conversations"]
users_collection = db["users"]
user_logs_collection = db["user_logs"]
user_tools_collection = db["user_tools"]
attachments_collection = db["attachments"]
workflow_runs_collection = db["workflow_runs"]
workflows_collection = db["workflows"]
workflow_nodes_collection = db["workflow_nodes"]
workflow_edges_collection = db["workflow_edges"]
try:
agents_collection.create_index(
[("shared", 1)],
name="shared_index",
background=True,
)
users_collection.create_index("user_id", unique=True)
workflows_collection.create_index(
[("user", 1)], name="workflow_user_index", background=True
)
workflow_nodes_collection.create_index(
[("workflow_id", 1)], name="node_workflow_index", background=True
)
workflow_nodes_collection.create_index(
[("workflow_id", 1), ("graph_version", 1)],
name="node_workflow_graph_version_index",
background=True,
)
workflow_edges_collection.create_index(
[("workflow_id", 1)], name="edge_workflow_index", background=True
)
workflow_edges_collection.create_index(
[("workflow_id", 1), ("graph_version", 1)],
name="edge_workflow_graph_version_index",
background=True,
)
except Exception as e:
print("Error creating indexes:", e)
current_dir = os.path.dirname(
os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
)
def generate_minute_range(start_date, end_date):
"""Generate a dictionary with minute-level time ranges."""
return {
(start_date + datetime.timedelta(minutes=i)).strftime("%Y-%m-%d %H:%M:00"): 0
for i in range(int((end_date - start_date).total_seconds() // 60) + 1)
}
def generate_hourly_range(start_date, end_date):
"""Generate a dictionary with hourly time ranges."""
return {
(start_date + datetime.timedelta(hours=i)).strftime("%Y-%m-%d %H:00"): 0
for i in range(int((end_date - start_date).total_seconds() // 3600) + 1)
}
def generate_date_range(start_date, end_date):
"""Generate a dictionary with daily date ranges."""
return {
(start_date + datetime.timedelta(days=i)).strftime("%Y-%m-%d"): 0
for i in range((end_date - start_date).days + 1)
}
def ensure_user_doc(user_id):
"""
Ensure user document exists with proper agent preferences structure.
Args:
user_id: The user ID to ensure
Returns:
The user document
"""
default_prefs = {
"pinned": [],
"shared_with_me": [],
}
user_doc = users_collection.find_one_and_update(
{"user_id": user_id},
{"$setOnInsert": {"agent_preferences": default_prefs}},
upsert=True,
return_document=ReturnDocument.AFTER,
)
prefs = user_doc.get("agent_preferences", {})
updates = {}
if "pinned" not in prefs:
updates["agent_preferences.pinned"] = []
if "shared_with_me" not in prefs:
updates["agent_preferences.shared_with_me"] = []
if updates:
users_collection.update_one({"user_id": user_id}, {"$set": updates})
user_doc = users_collection.find_one({"user_id": user_id})
return user_doc
def resolve_tool_details(tool_ids):
"""
Resolve tool IDs to their details.
Args:
tool_ids: List of tool IDs
Returns:
List of tool details with id, name, and display_name
"""
tools = user_tools_collection.find(
{"_id": {"$in": [ObjectId(tid) for tid in tool_ids]}}
)
return [
{
"id": str(tool["_id"]),
"name": tool.get("name", ""),
"display_name": tool.get("displayName", tool.get("name", "")),
}
for tool in tools
]
def get_vector_store(source_id):
"""
Get the Vector Store for a given source ID.
Args:
source_id (str): source id of the document
Returns:
Vector store instance
"""
store = VectorCreator.create_vectorstore(
settings.VECTOR_STORE,
source_id=source_id,
embeddings_key=os.getenv("EMBEDDINGS_KEY"),
)
return store
def handle_image_upload(
request, existing_url: str, user: str, storage, base_path: str = "attachments/"
) -> Tuple[str, Optional[Response]]:
"""
Handle image file upload from request.
Args:
request: Flask request object
existing_url: Existing image URL (fallback)
user: User ID
storage: Storage instance
base_path: Base path for upload
Returns:
Tuple of (image_url, error_response)
"""
image_url = existing_url
if "image" in request.files:
file = request.files["image"]
if file.filename != "":
filename = secure_filename(file.filename)
upload_path = f"{settings.UPLOAD_FOLDER.rstrip('/')}/{user}/{base_path.rstrip('/')}/{uuid.uuid4()}_{filename}"
try:
storage.save_file(file, upload_path, storage_class="STANDARD")
image_url = upload_path
except Exception as e:
current_app.logger.error(f"Error uploading image: {e}")
return None, make_response(
jsonify({"success": False, "message": "Image upload failed"}),
400,
)
return image_url, None
def require_agent(func):
"""
Decorator to require valid agent webhook token.
Args:
func: Function to decorate
Returns:
Wrapped function
"""
@wraps(func)
def wrapper(*args, **kwargs):
webhook_token = kwargs.get("webhook_token")
if not webhook_token:
return make_response(
jsonify({"success": False, "message": "Webhook token missing"}), 400
)
agent = agents_collection.find_one(
{"incoming_webhook_token": webhook_token}, {"_id": 1}
)
if not agent:
current_app.logger.warning(
f"Webhook attempt with invalid token: {webhook_token}"
)
return make_response(
jsonify({"success": False, "message": "Agent not found"}), 404
)
kwargs["agent"] = agent
kwargs["agent_id_str"] = str(agent["_id"])
return func(*args, **kwargs)
return wrapper