""" E2E Test Data Creator for AutoGPT Platform This script creates test data for E2E tests by using API functions instead of direct Prisma calls. This approach ensures compatibility with future model changes by using the API layer. Image/Video URL Domains Used: - Images: picsum.photos (for all image URLs - avatars, store listing images, etc.) - Videos: youtube.com (for store listing video URLs) Add these domains to your Next.js config: ```javascript // next.config.js images: { domains: ['picsum.photos'], } ``` """ import asyncio import random from typing import Any, Dict, List from faker import Faker # Import API functions from the backend from backend.api.features.library.db import create_library_agent, create_preset from backend.api.features.library.model import LibraryAgentPresetCreatable from backend.api.features.store.db import ( create_store_submission, review_store_submission, ) from backend.data.auth.api_key import create_api_key from backend.data.credit import get_user_credit_model from backend.data.db import prisma from backend.data.graph import Graph, Link, Node, create_graph from backend.data.user import get_or_create_user from backend.util.clients import get_supabase faker = Faker() # Constants for data generation limits (reduced for E2E tests) NUM_USERS = 15 NUM_AGENT_BLOCKS = 30 MIN_GRAPHS_PER_USER = 25 MAX_GRAPHS_PER_USER = 25 MIN_NODES_PER_GRAPH = 3 MAX_NODES_PER_GRAPH = 6 MIN_PRESETS_PER_USER = 2 MAX_PRESETS_PER_USER = 3 MIN_AGENTS_PER_USER = 25 MAX_AGENTS_PER_USER = 25 MIN_EXECUTIONS_PER_GRAPH = 2 MAX_EXECUTIONS_PER_GRAPH = 8 MIN_REVIEWS_PER_VERSION = 2 MAX_REVIEWS_PER_VERSION = 5 # Guaranteed minimums for marketplace tests (deterministic) GUARANTEED_FEATURED_AGENTS = 8 GUARANTEED_FEATURED_CREATORS = 5 GUARANTEED_TOP_AGENTS = 10 def get_image(): """Generate a consistent image URL using picsum.photos service.""" width = random.choice([200, 300, 400, 500, 600, 800]) height = random.choice([200, 300, 400, 500, 600, 800]) seed = random.randint(1, 1000) return f"https://picsum.photos/seed/{seed}/{width}/{height}" def get_video_url(): """Generate a consistent video URL using YouTube.""" video_ids = [ "dQw4w9WgXcQ", "9bZkp7q19f0", "kJQP7kiw5Fk", "RgKAFK5djSk", "L_jWHffIx5E", ] video_id = random.choice(video_ids) return f"https://www.youtube.com/watch?v={video_id}" def get_category(): """Generate a random category from the predefined list.""" categories = [ "productivity", "writing", "development", "data", "marketing", "research", "creative", "business", "personal", "other", ] return random.choice(categories) class TestDataCreator: """Creates test data using API functions for E2E tests.""" def __init__(self): self.users: List[Dict[str, Any]] = [] self.agent_blocks: List[Dict[str, Any]] = [] self.agent_graphs: List[Dict[str, Any]] = [] self.library_agents: List[Dict[str, Any]] = [] self.store_submissions: List[Dict[str, Any]] = [] self.api_keys: List[Dict[str, Any]] = [] self.presets: List[Dict[str, Any]] = [] self.profiles: List[Dict[str, Any]] = [] async def create_test_users(self) -> List[Dict[str, Any]]: """Create test users using Supabase client.""" print(f"Creating {NUM_USERS} test users...") supabase = get_supabase() users = [] for i in range(NUM_USERS): try: # Generate test user data if i == 0: # First user should have test123@gmail.com email for testing email = "test123@gmail.com" else: email = faker.unique.email() password = "testpassword123" # Standard test password user_id = f"test-user-{i}-{faker.uuid4()}" # Create user in Supabase Auth (if needed) try: auth_response = supabase.auth.admin.create_user( {"email": email, "password": password, "email_confirm": True} ) if auth_response.user: user_id = auth_response.user.id except Exception as supabase_error: print( f"Supabase user creation failed for {email}, using fallback: {supabase_error}" ) # Fall back to direct database creation # Create mock user data similar to what auth middleware would provide user_data = { "sub": user_id, "email": email, } # Use the API function to create user in local database user = await get_or_create_user(user_data) users.append(user.model_dump()) except Exception as e: print(f"Error creating user {i}: {e}") continue self.users = users return users async def get_available_blocks(self) -> List[Dict[str, Any]]: """Get available agent blocks from database.""" print("Getting available agent blocks...") # Get blocks from database instead of the registry db_blocks = await prisma.agentblock.find_many() if not db_blocks: print("No blocks found in database, creating some basic blocks...") # Create some basic blocks if none exist from backend.blocks.io import AgentInputBlock, AgentOutputBlock from backend.blocks.maths import CalculatorBlock from backend.blocks.time_blocks import GetCurrentTimeBlock blocks_to_create = [ AgentInputBlock(), AgentOutputBlock(), CalculatorBlock(), GetCurrentTimeBlock(), ] for block in blocks_to_create: try: await prisma.agentblock.create( data={ "id": block.id, "name": block.name, "inputSchema": "{}", "outputSchema": "{}", } ) except Exception as e: print(f"Error creating block {block.name}: {e}") # Get blocks again after creation db_blocks = await prisma.agentblock.find_many() self.agent_blocks = [ {"id": block.id, "name": block.name} for block in db_blocks ] print(f"Found {len(self.agent_blocks)} blocks in database") return self.agent_blocks async def create_test_graphs(self) -> List[Dict[str, Any]]: """Create test graphs using the API function.""" print("Creating test graphs...") graphs = [] for user in self.users: num_graphs = random.randint(MIN_GRAPHS_PER_USER, MAX_GRAPHS_PER_USER) for graph_num in range(num_graphs): # Create a simple graph with nodes and links graph_id = str(faker.uuid4()) nodes = [] links = [] # Determine if this should be a DummyInput graph (first 3-4 graphs per user) is_dummy_input = graph_num < 4 # Create nodes based on graph type if is_dummy_input: # For dummy input graphs: only GetCurrentTimeBlock node_id = str(faker.uuid4()) block = next( b for b in self.agent_blocks if b["name"] == "GetCurrentTimeBlock" ) input_default = {"trigger": "start", "format": "%H:%M:%S"} node = Node( id=node_id, block_id=block["id"], input_default=input_default, metadata={"position": {"x": 0, "y": 0}}, ) nodes.append(node) else: # For regular graphs: Create calculator agent pattern with 4 nodes # Node 1: AgentInputBlock for 'a' input_a_id = str(faker.uuid4()) input_a_block = next( b for b in self.agent_blocks if b["name"] == "AgentInputBlock" ) input_a_node = Node( id=input_a_id, block_id=input_a_block["id"], input_default={ "name": "a", "title": None, "value": "", "advanced": False, "description": None, "placeholder_values": [], }, metadata={"position": {"x": -1012, "y": 674}}, ) nodes.append(input_a_node) # Node 2: AgentInputBlock for 'b' input_b_id = str(faker.uuid4()) input_b_block = next( b for b in self.agent_blocks if b["name"] == "AgentInputBlock" ) input_b_node = Node( id=input_b_id, block_id=input_b_block["id"], input_default={ "name": "b", "title": None, "value": "", "advanced": False, "description": None, "placeholder_values": [], }, metadata={"position": {"x": -1117, "y": 78}}, ) nodes.append(input_b_node) # Node 3: CalculatorBlock calc_id = str(faker.uuid4()) calc_block = next( b for b in self.agent_blocks if b["name"] == "CalculatorBlock" ) calc_node = Node( id=calc_id, block_id=calc_block["id"], input_default={"operation": "Add", "round_result": False}, metadata={"position": {"x": -435, "y": 363}}, ) nodes.append(calc_node) # Node 4: AgentOutputBlock output_id = str(faker.uuid4()) output_block = next( b for b in self.agent_blocks if b["name"] == "AgentOutputBlock" ) output_node = Node( id=output_id, block_id=output_block["id"], input_default={ "name": "result", "title": None, "value": "", "format": "", "advanced": False, "description": None, }, metadata={"position": {"x": 402, "y": 0}}, ) nodes.append(output_node) # Create links between nodes (only for non-dummy graphs with multiple nodes) if len(nodes) >= 4: # Use the actual node IDs from the created nodes instead of our variables actual_input_a_id = nodes[0].id # First node (input_a) actual_input_b_id = nodes[1].id # Second node (input_b) actual_calc_id = nodes[2].id # Third node (calculator) actual_output_id = nodes[3].id # Fourth node (output) # Link input_a to calculator.a link1 = Link( source_id=actual_input_a_id, sink_id=actual_calc_id, source_name="result", sink_name="a", is_static=True, ) links.append(link1) # Link input_b to calculator.b link2 = Link( source_id=actual_input_b_id, sink_id=actual_calc_id, source_name="result", sink_name="b", is_static=True, ) links.append(link2) # Link calculator.result to output.value link3 = Link( source_id=actual_calc_id, sink_id=actual_output_id, source_name="result", sink_name="value", is_static=False, ) links.append(link3) # Create graph object with DummyInput in name if it's a dummy input graph graph_name = faker.sentence(nb_words=3) if is_dummy_input: graph_name = f"DummyInput {graph_name}" graph_name = f"{graph_name} Agents" graph = Graph( id=graph_id, name=graph_name, description=faker.text(max_nb_chars=200), nodes=nodes, links=links, is_active=True, ) try: # Use the API function to create graph created_graph = await create_graph(graph, user["id"]) graph_dict = created_graph.model_dump() # Ensure userId is included for store submissions graph_dict["userId"] = user["id"] graphs.append(graph_dict) print( f"āœ… Created graph for user {user['id']}: {graph_dict['name']}" ) except Exception as e: print(f"Error creating graph: {e}") continue self.agent_graphs = graphs return graphs async def create_test_library_agents(self) -> List[Dict[str, Any]]: """Create test library agents using the API function.""" print("Creating test library agents...") library_agents = [] for user in self.users: num_agents = random.randint(MIN_AGENTS_PER_USER, MAX_AGENTS_PER_USER) # Get available graphs for this user user_graphs = [ g for g in self.agent_graphs if g.get("userId") == user["id"] ] if not user_graphs: continue # Shuffle and take unique graphs to avoid duplicates random.shuffle(user_graphs) selected_graphs = user_graphs[: min(num_agents, len(user_graphs))] for graph_data in selected_graphs: try: # Get the graph model from the database from backend.data.graph import get_graph graph = await get_graph( graph_data["id"], graph_data.get("version", 1), user_id=user["id"], ) if graph: # Use the API function to create library agent library_agents.extend( v.model_dump() for v in await create_library_agent(graph, user["id"]) ) except Exception as e: print(f"Error creating library agent: {e}") continue self.library_agents = library_agents return library_agents async def create_test_presets(self) -> List[Dict[str, Any]]: """Create test presets using the API function.""" print("Creating test presets...") presets = [] for user in self.users: num_presets = random.randint(MIN_PRESETS_PER_USER, MAX_PRESETS_PER_USER) # Get available graphs for this user user_graphs = [ g for g in self.agent_graphs if g.get("userId") == user["id"] ] if not user_graphs: continue for _ in range(min(num_presets, len(user_graphs))): graph = random.choice(user_graphs) preset_data = LibraryAgentPresetCreatable( name=faker.sentence(nb_words=3), description=faker.text(max_nb_chars=200), graph_id=graph["id"], # Fixed field name graph_version=graph.get("version", 1), # Fixed field name inputs={}, # Required field - empty inputs for test data credentials={}, # Required field - empty credentials for test data is_active=True, ) try: # Use the API function to create preset preset = await create_preset(user["id"], preset_data) presets.append(preset.model_dump()) except Exception as e: print(f"Error creating preset: {e}") continue self.presets = presets return presets async def create_test_api_keys(self) -> List[Dict[str, Any]]: """Create test API keys using the API function.""" print("Creating test API keys...") api_keys = [] for user in self.users: from backend.data.auth.api_key import APIKeyPermission try: # Use the API function to create API key api_key, _ = await create_api_key( name=faker.word(), user_id=user["id"], permissions=[ APIKeyPermission.EXECUTE_GRAPH, APIKeyPermission.READ_GRAPH, ], description=faker.text(), ) api_keys.append(api_key.model_dump()) except Exception as e: print(f"Error creating API key for user {user['id']}: {e}") continue self.api_keys = api_keys return api_keys async def update_test_profiles(self) -> List[Dict[str, Any]]: """Update existing user profiles to make some into featured creators.""" print("Updating user profiles to create featured creators...") # Get all existing profiles (auto-created when users were created) existing_profiles = await prisma.profile.find_many( where={"userId": {"in": [user["id"] for user in self.users]}} ) if not existing_profiles: print("No existing profiles found. Profiles may not be auto-created.") return [] profiles = [] # Select about 70% of users to become creators (update their profiles) num_creators = max(1, int(len(existing_profiles) * 0.7)) selected_profiles = random.sample( existing_profiles, min(num_creators, len(existing_profiles)) ) # Guarantee at least GUARANTEED_FEATURED_CREATORS featured creators num_featured = max(GUARANTEED_FEATURED_CREATORS, int(num_creators * 0.5)) num_featured = min( num_featured, len(selected_profiles) ) # Don't exceed available profiles featured_profile_ids = set( random.sample([p.id for p in selected_profiles], num_featured) ) print( f"šŸŽÆ Creating {num_featured} featured creators (min: {GUARANTEED_FEATURED_CREATORS})" ) for profile in selected_profiles: try: is_featured = profile.id in featured_profile_ids # Update the profile with creator data updated_profile = await prisma.profile.update( where={"id": profile.id}, data={ "name": faker.name(), "username": faker.user_name() + str(random.randint(100, 999)), # Ensure uniqueness "description": faker.text(max_nb_chars=200), "links": [faker.url() for _ in range(random.randint(1, 3))], "avatarUrl": get_image(), "isFeatured": is_featured, }, ) if updated_profile: profiles.append(updated_profile.model_dump()) except Exception as e: print(f"Error updating profile {profile.id}: {e}") continue self.profiles = profiles return profiles async def create_test_store_submissions(self) -> List[Dict[str, Any]]: """Create test store submissions using the API function. DETERMINISTIC: Guarantees minimum featured agents for E2E tests. """ print("Creating test store submissions...") submissions = [] approved_submissions = [] featured_count = 0 submission_counter = 0 # Create a special test submission for test123@gmail.com (ALWAYS approved + featured) test_user = next( (user for user in self.users if user["email"] == "test123@gmail.com"), None ) if test_user and self.agent_graphs: test_submission_data = { "user_id": test_user["id"], "agent_id": self.agent_graphs[0]["id"], "agent_version": 1, "slug": "test-agent-submission", "name": "Test Agent Submission", "sub_heading": "A test agent for frontend testing", "video_url": "https://www.youtube.com/watch?v=test123", "image_urls": [ "https://picsum.photos/200/300", "https://picsum.photos/200/301", "https://picsum.photos/200/302", ], "description": "This is a test agent submission specifically created for frontend testing purposes.", "categories": ["test", "demo", "frontend"], "changes_summary": "Initial test submission", } try: test_submission = await create_store_submission(**test_submission_data) submissions.append(test_submission.model_dump()) print("āœ… Created special test store submission for test123@gmail.com") # ALWAYS approve and feature the test submission if test_submission.store_listing_version_id: approved_submission = await review_store_submission( store_listing_version_id=test_submission.store_listing_version_id, is_approved=True, external_comments="Test submission approved", internal_comments="Auto-approved test submission", reviewer_id=test_user["id"], ) approved_submissions.append(approved_submission.model_dump()) print("āœ… Approved test store submission") await prisma.storelistingversion.update( where={"id": test_submission.store_listing_version_id}, data={"isFeatured": True}, ) featured_count += 1 print("🌟 Marked test agent as FEATURED") except Exception as e: print(f"Error creating test store submission: {e}") import traceback traceback.print_exc() # Create regular submissions for all users for user in self.users: user_graphs = [ g for g in self.agent_graphs if g.get("userId") == user["id"] ] print(f"User {user['id']} has {len(user_graphs)} graphs") if not user_graphs: print( f"No graphs found for user {user['id']}, skipping store submissions" ) continue for submission_index in range(4): graph = random.choice(user_graphs) submission_counter += 1 try: print( f"Creating store submission for user {user['id']} with graph {graph['id']}" ) submission = await create_store_submission( user_id=user["id"], agent_id=graph["id"], agent_version=graph.get("version", 1), slug=faker.slug(), name=graph.get("name", faker.sentence(nb_words=3)), sub_heading=faker.sentence(), video_url=get_video_url() if random.random() < 0.3 else None, image_urls=[get_image() for _ in range(3)], description=faker.text(), categories=[get_category()], changes_summary="Initial E2E test submission", ) submissions.append(submission.model_dump()) print(f"āœ… Created store submission: {submission.name}") if submission.store_listing_version_id: # DETERMINISTIC: First N submissions are always approved # First GUARANTEED_FEATURED_AGENTS of those are always featured should_approve = ( submission_counter <= GUARANTEED_TOP_AGENTS or random.random() < 0.4 ) should_feature = featured_count < GUARANTEED_FEATURED_AGENTS if should_approve: try: reviewer_id = random.choice(self.users)["id"] approved_submission = await review_store_submission( store_listing_version_id=submission.store_listing_version_id, is_approved=True, external_comments="Auto-approved for E2E testing", internal_comments="Automatically approved by E2E test data script", reviewer_id=reviewer_id, ) approved_submissions.append( approved_submission.model_dump() ) print( f"āœ… Approved store submission: {submission.name}" ) if should_feature: try: await prisma.storelistingversion.update( where={ "id": submission.store_listing_version_id }, data={"isFeatured": True}, ) featured_count += 1 print( f"🌟 Marked agent as FEATURED ({featured_count}/{GUARANTEED_FEATURED_AGENTS}): {submission.name}" ) except Exception as e: print( f"Warning: Could not mark submission as featured: {e}" ) elif random.random() < 0.2: try: await prisma.storelistingversion.update( where={ "id": submission.store_listing_version_id }, data={"isFeatured": True}, ) featured_count += 1 print( f"🌟 Marked agent as FEATURED (bonus): {submission.name}" ) except Exception as e: print( f"Warning: Could not mark submission as featured: {e}" ) except Exception as e: print( f"Warning: Could not approve submission {submission.name}: {e}" ) elif random.random() < 0.5: try: reviewer_id = random.choice(self.users)["id"] await review_store_submission( store_listing_version_id=submission.store_listing_version_id, is_approved=False, external_comments="Submission rejected - needs improvements", internal_comments="Automatically rejected by E2E test data script", reviewer_id=reviewer_id, ) print( f"āŒ Rejected store submission: {submission.name}" ) except Exception as e: print( f"Warning: Could not reject submission {submission.name}: {e}" ) else: print( f"ā³ Left submission pending for review: {submission.name}" ) except Exception as e: print( f"Error creating store submission for user {user['id']} graph {graph['id']}: {e}" ) import traceback traceback.print_exc() continue print("\nšŸ“Š Store Submissions Summary:") print(f" Created: {len(submissions)}") print(f" Approved: {len(approved_submissions)}") print( f" Featured: {featured_count} (guaranteed min: {GUARANTEED_FEATURED_AGENTS})" ) self.store_submissions = submissions return submissions async def add_user_credits(self): """Add credits to users.""" print("Adding credits to users...") for user in self.users: try: # Get user-specific credit model credit_model = await get_user_credit_model(user["id"]) # Skip credits for disabled credit model to avoid errors if ( hasattr(credit_model, "__class__") and "Disabled" in credit_model.__class__.__name__ ): print(f"Skipping credits for user {user['id']} - credits disabled") continue # Add random credits to each user credit_amount = random.randint(100, 1000) await credit_model.top_up_credits( user_id=user["id"], amount=credit_amount ) print(f"Added {credit_amount} credits to user {user['id']}") except Exception: print( f"Skipping credits for user {user['id']}: credits may be disabled" ) continue async def create_all_test_data(self): """Create all test data.""" print("Starting E2E test data creation...") # Create users first await self.create_test_users() # Get available blocks await self.get_available_blocks() # Create graphs await self.create_test_graphs() # Create library agents await self.create_test_library_agents() # Create presets await self.create_test_presets() # Create API keys await self.create_test_api_keys() # Update user profiles to create featured creators await self.update_test_profiles() # Create store submissions await self.create_test_store_submissions() # Add user credits await self.add_user_credits() # Refresh materialized views print("Refreshing materialized views...") try: await prisma.execute_raw("SELECT refresh_store_materialized_views();") except Exception as e: print(f"Error refreshing materialized views: {e}") print("E2E test data creation completed successfully!") # Print summary print("\nšŸŽ‰ E2E Test Data Creation Summary:") print(f"āœ… Users created: {len(self.users)}") print(f"āœ… Agent blocks available: {len(self.agent_blocks)}") print(f"āœ… Agent graphs created: {len(self.agent_graphs)}") print(f"āœ… Library agents created: {len(self.library_agents)}") print(f"āœ… Creator profiles updated: {len(self.profiles)}") print(f"āœ… Store submissions created: {len(self.store_submissions)}") print(f"āœ… API keys created: {len(self.api_keys)}") print(f"āœ… Presets created: {len(self.presets)}") print("\nšŸŽÆ Deterministic Guarantees:") print(f" • Featured agents: >= {GUARANTEED_FEATURED_AGENTS}") print(f" • Featured creators: >= {GUARANTEED_FEATURED_CREATORS}") print(f" • Top agents (approved): >= {GUARANTEED_TOP_AGENTS}") print(f" • Library agents per user: >= {MIN_AGENTS_PER_USER}") print("\nšŸš€ Your E2E test database is ready to use!") async def main(): """Main function to run the test data creation.""" # Connect to database await prisma.connect() try: creator = TestDataCreator() await creator.create_all_test_data() finally: # Disconnect from database await prisma.disconnect() if __name__ == "__main__": asyncio.run(main())