"""
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: none. Avatars and store listing images are seeded empty so the
  frontend renders its built-in solid-color/boring-avatars fallback. This
  avoids any external image dependency (e.g. picsum.photos) that intermittently
  504'd through Next's /_next/image optimizer and stalled E2E navigations.
- Videos: youtube.com (for store listing video URLs)
"""

import asyncio
import json
import random
from pathlib import Path
from typing import Any, Dict, List

import prisma.enums as prisma_enums
import prisma.models as prisma_models
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.api.features.store.model import StoreSubmission
from backend.blocks.io import AgentInputBlock
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, make_graph_model
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
E2E_MARKETPLACE_CREATOR_EMAIL = "test123@example.com"
E2E_MARKETPLACE_CREATOR_USERNAME = "e2e-marketplace"
E2E_MARKETPLACE_AGENT_SLUG = "e2e-calculator-agent"
E2E_MARKETPLACE_AGENT_NAME = "E2E Calculator Agent"
E2E_MARKETPLACE_AGENT_INPUT_VALUE = 8
E2E_MARKETPLACE_AGENT_OUTPUT_VALUE = 42
_LOCAL_TEMPLATE_PATH = (
    Path(__file__).resolve().parents[1] / "agents" / "calculator-agent.json"
)
_DOCKER_TEMPLATE_PATH = Path(
    "/app/autogpt_platform/backend/agents/calculator-agent.json"
)
E2E_MARKETPLACE_AGENT_TEMPLATE_PATH = (
    _LOCAL_TEMPLATE_PATH if _LOCAL_TEMPLATE_PATH.exists() else _DOCKER_TEMPLATE_PATH
)
SEEDED_TEST_EMAILS = [
    "test123@example.com",
    "e2e.qa.auth@example.com",
    "e2e.qa.builder@example.com",
    "e2e.qa.library@example.com",
    "e2e.qa.marketplace@example.com",
    "e2e.qa.settings@example.com",
    "e2e.qa.parallel.a@example.com",
    "e2e.qa.parallel.b@example.com",
]


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)


def load_deterministic_marketplace_graph() -> Graph:
    graph = Graph.model_validate(
        json.loads(E2E_MARKETPLACE_AGENT_TEMPLATE_PATH.read_text())
    )
    graph.name = E2E_MARKETPLACE_AGENT_NAME
    graph.description = (
        "Deterministic marketplace calculator graph for Playwright PR E2E coverage."
    )

    for node in graph.nodes:
        if (
            node.block_id == AgentInputBlock().id
            and node.input_default.get("value") is None
        ):
            node.input_default["value"] = E2E_MARKETPLACE_AGENT_INPUT_VALUE

    return graph


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 < len(SEEDED_TEST_EMAILS):
                    # Keep a deterministic pool for Playwright global setup and PR smoke flows
                    email = SEEDED_TEST_EMAILS[i]
                else:
                    email = faker.unique.email()
                password = "testpassword123"  # Standard test password # pragma: allowlist secret # noqa
                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,
                        },
                        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,
                        },
                        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"✅ 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"🎯 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))],
                        # Empty (not None): the Creator view types avatar_url as
                        # non-nullable, so null breaks /api/store/creators. Empty
                        # string renders the frontend's fallback avatar.
                        "avatarUrl": "",
                        "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

        deterministic_creator = next(
            (
                user
                for user in self.users
                if user["email"] == E2E_MARKETPLACE_CREATOR_EMAIL
            ),
            None,
        )
        if deterministic_creator:
            deterministic_profile = next(
                (
                    profile
                    for profile in existing_profiles
                    if profile.userId == deterministic_creator["id"]
                ),
                None,
            )
            if deterministic_profile:
                try:
                    updated_profile = await prisma.profile.update(
                        where={"id": deterministic_profile.id},
                        data={
                            "name": "E2E Marketplace Creator",
                            "username": E2E_MARKETPLACE_CREATOR_USERNAME,
                            "description": "Deterministic marketplace creator for Playwright PR E2E coverage.",
                            "links": ["https://example.com/e2e-marketplace"],
                            # Empty (not None) — Creator view requires non-null avatar_url.
                            "avatarUrl": "",
                            "isFeatured": True,
                        },
                    )
                    profiles = [
                        profile
                        for profile in profiles
                        if profile.get("id") != deterministic_profile.id
                    ]
                    if updated_profile is not None:
                        profiles.append(updated_profile.model_dump())
                except Exception as e:
                    print(f"Error updating deterministic E2E creator profile: {e}")

        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 deterministic calculator marketplace agent for PR E2E coverage
        test_user = next(
            (
                user
                for user in self.users
                if user["email"] == E2E_MARKETPLACE_CREATOR_EMAIL
            ),
            None,
        )
        if test_user:
            deterministic_graph = None

            try:
                existing_graph = await prisma_models.AgentGraph.prisma().find_first(
                    where={
                        "userId": test_user["id"],
                        "name": E2E_MARKETPLACE_AGENT_NAME,
                        "isActive": True,
                    },
                    order={"version": "desc"},
                )
                if existing_graph:
                    deterministic_graph = {
                        "id": existing_graph.id,
                        "version": existing_graph.version,
                        "name": existing_graph.name,
                        "userId": test_user["id"],
                    }
                    self.agent_graphs.append(deterministic_graph)
                    print(
                        "✅ Reused existing deterministic marketplace graph: "
                        f"{existing_graph.id}"
                    )
                else:
                    deterministic_graph_model = make_graph_model(
                        load_deterministic_marketplace_graph(),
                        test_user["id"],
                    )
                    deterministic_graph_model.reassign_ids(
                        user_id=test_user["id"],
                        reassign_graph_id=True,
                    )
                    created_deterministic_graph = await create_graph(
                        deterministic_graph_model,
                        test_user["id"],
                    )
                    deterministic_graph = created_deterministic_graph.model_dump()
                    deterministic_graph["userId"] = test_user["id"]
                    self.agent_graphs.append(deterministic_graph)
                    print("✅ Created deterministic marketplace graph")
            except Exception as e:
                print(f"Error creating deterministic marketplace graph: {e}")

            if deterministic_graph is None and self.agent_graphs:
                test_user_graphs = [
                    graph
                    for graph in self.agent_graphs
                    if graph.get("userId") == test_user["id"]
                ]
                deterministic_graph = next(
                    (
                        graph
                        for graph in test_user_graphs
                        if not graph.get("name", "").startswith("DummyInput ")
                    ),
                    test_user_graphs[0] if test_user_graphs else None,
                )

            if deterministic_graph:
                test_submission_data = {
                    "user_id": test_user["id"],
                    "graph_id": deterministic_graph["id"],
                    "graph_version": deterministic_graph.get("version", 1),
                    "slug": E2E_MARKETPLACE_AGENT_SLUG,
                    "name": E2E_MARKETPLACE_AGENT_NAME,
                    "sub_heading": "A deterministic calculator agent for PR E2E coverage",
                    "video_url": "https://www.youtube.com/watch?v=test123",
                    "image_urls": [],
                    "description": (
                        "A deterministic marketplace calculator agent that adds "
                        f"{E2E_MARKETPLACE_AGENT_INPUT_VALUE} and 34 to produce "
                        f"{E2E_MARKETPLACE_AGENT_OUTPUT_VALUE} for frontend E2E coverage."
                    ),
                    "categories": ["test", "demo", "frontend"],
                    "changes_summary": (
                        "Initial deterministic calculator submission seeded from "
                        "backend/agents/calculator-agent.json"
                    ),
                }

                try:
                    existing_deterministic_submission = (
                        await prisma_models.StoreListingVersion.prisma().find_first(
                            where={
                                "isDeleted": False,
                                "StoreListing": {
                                    "is": {
                                        "owningUserId": test_user["id"],
                                        "slug": E2E_MARKETPLACE_AGENT_SLUG,
                                        "isDeleted": False,
                                    }
                                },
                            },
                            include={"StoreListing": True},
                            order={"version": "desc"},
                        )
                    )

                    if existing_deterministic_submission:
                        test_submission = StoreSubmission.from_listing_version(
                            existing_deterministic_submission
                        )
                        submissions.append(test_submission.model_dump())
                        print(
                            "✅ Reused deterministic marketplace submission: "
                            f"{E2E_MARKETPLACE_AGENT_NAME}"
                        )
                    else:
                        test_submission = await create_store_submission(
                            **test_submission_data
                        )
                        submissions.append(test_submission.model_dump())
                        print(
                            "✅ Created deterministic marketplace submission: "
                            f"{E2E_MARKETPLACE_AGENT_NAME}"
                        )

                    current_status = (
                        existing_deterministic_submission.submissionStatus
                        if existing_deterministic_submission
                        else test_submission.status
                    )
                    is_featured = bool(
                        existing_deterministic_submission
                        and existing_deterministic_submission.isFeatured
                    )

                    if test_submission.listing_version_id:
                        if current_status != prisma_enums.SubmissionStatus.APPROVED:
                            approved_submission = await review_store_submission(
                                store_listing_version_id=test_submission.listing_version_id,
                                is_approved=True,
                                external_comments="Deterministic calculator submission approved",
                                internal_comments="Auto-approved PR E2E marketplace submission",
                                reviewer_id=test_user["id"],
                            )
                            approved_submissions.append(
                                approved_submission.model_dump()
                            )
                            print("✅ Approved deterministic marketplace submission")
                        else:
                            approved_submissions.append(test_submission.model_dump())
                            print(
                                "✅ Deterministic marketplace submission already approved"
                            )

                        if is_featured:
                            featured_count += 1
                            print("🌟 Deterministic marketplace agent already FEATURED")
                        else:
                            await prisma.storelistingversion.update(
                                where={"id": test_submission.listing_version_id},
                                data={"isFeatured": True},
                            )
                            featured_count += 1
                            print(
                                "🌟 Marked deterministic marketplace agent as FEATURED"
                            )

                except Exception as e:
                    print(f"Error creating deterministic marketplace 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"],
                        graph_id=graph["id"],
                        graph_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=[],
                        description=faker.text(),
                        categories=[get_category()],
                        changes_summary="Initial E2E test submission",
                    )
                    submissions.append(submission.model_dump())
                    print(f"✅ Created store submission: {submission.name}")

                    if submission.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.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"✅ Approved store submission: {submission.name}"
                                )

                                if should_feature:
                                    try:
                                        await prisma.storelistingversion.update(
                                            where={"id": submission.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.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.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"❌ Rejected store submission: {submission.name}"
                                )
                            except Exception as e:
                                print(
                                    f"Warning: Could not reject submission {submission.name}: {e}"
                                )
                        else:
                            print(
                                f"⏳ 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("\n📊 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("\n🎉 E2E Test Data Creation Summary:")
        print(f"✅ Users created: {len(self.users)}")
        print(f"✅ Agent blocks available: {len(self.agent_blocks)}")
        print(f"✅ Agent graphs created: {len(self.agent_graphs)}")
        print(f"✅ Library agents created: {len(self.library_agents)}")
        print(f"✅ Creator profiles updated: {len(self.profiles)}")
        print(f"✅ Store submissions created: {len(self.store_submissions)}")
        print(f"✅ API keys created: {len(self.api_keys)}")
        print(f"✅ Presets created: {len(self.presets)}")
        print("\n🎯 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("\n🚀 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())
