added prisma schame changes and understanding tool

This commit is contained in:
Swifty
2026-01-07 10:02:44 +01:00
parent d3dd13fc55
commit e8b878521f
4 changed files with 765 additions and 41 deletions

View File

@@ -6,12 +6,11 @@ start-core:
# Stop core services
stop-core:
docker compose stop deps
docker compose stop
reset-db:
docker compose stop db
rm -rf db/docker/volumes/db/data
cd backend && poetry run prisma migrate deploy
cd backend && poetry run prisma generate
# View logs for core services
logs-core:
@@ -58,4 +57,4 @@ help:
@echo " run-backend - Run the backend FastAPI server"
@echo " run-frontend - Run the frontend Next.js development server"
@echo " test-data - Run the test data creator"
@echo " load-store-agents - Load store agents from agents/ folder into test database"
@echo " load-store-agents - Load store agents from agents/ folder into test database"

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@@ -0,0 +1,206 @@
"""Tool for capturing user business understanding incrementally."""
import logging
from typing import Any
from backend.api.features.chat.model import ChatSession
from backend.data.understanding import (
BusinessUnderstandingInput,
upsert_business_understanding,
)
from .base import BaseTool
from .models import (
ErrorResponse,
ToolResponseBase,
UnderstandingUpdatedResponse,
)
logger = logging.getLogger(__name__)
class AddUnderstandingTool(BaseTool):
"""Tool for capturing user's business understanding incrementally."""
@property
def name(self) -> str:
return "add_understanding"
@property
def description(self) -> str:
return """Capture and store information about the user's business context,
workflows, pain points, and automation goals. Call this tool whenever the user
shares information about their business. Each call incrementally adds to the
existing understanding - you don't need to provide all fields at once.
Use this to build a comprehensive profile that helps recommend better agents
and automations for the user's specific needs."""
@property
def parameters(self) -> dict[str, Any]:
return {
"type": "object",
"properties": {
"user_name": {
"type": "string",
"description": "The user's name",
},
"job_title": {
"type": "string",
"description": "The user's job title (e.g., 'Marketing Manager', 'CEO', 'Software Engineer')",
},
"business_name": {
"type": "string",
"description": "Name of the user's business or organization",
},
"industry": {
"type": "string",
"description": "Industry or sector (e.g., 'e-commerce', 'healthcare', 'finance')",
},
"business_size": {
"type": "string",
"description": "Company size: '1-10', '11-50', '51-200', '201-1000', or '1000+'",
},
"user_role": {
"type": "string",
"description": "User's role in organization context (e.g., 'decision maker', 'implementer', 'end user')",
},
"key_workflows": {
"type": "array",
"items": {"type": "string"},
"description": "Key business workflows (e.g., 'lead qualification', 'content publishing')",
},
"daily_activities": {
"type": "array",
"items": {"type": "string"},
"description": "Regular daily activities the user performs",
},
"pain_points": {
"type": "array",
"items": {"type": "string"},
"description": "Current pain points or challenges",
},
"bottlenecks": {
"type": "array",
"items": {"type": "string"},
"description": "Process bottlenecks slowing things down",
},
"manual_tasks": {
"type": "array",
"items": {"type": "string"},
"description": "Manual or repetitive tasks that could be automated",
},
"automation_goals": {
"type": "array",
"items": {"type": "string"},
"description": "Desired automation outcomes or goals",
},
"current_software": {
"type": "array",
"items": {"type": "string"},
"description": "Software and tools currently in use",
},
"existing_automation": {
"type": "array",
"items": {"type": "string"},
"description": "Any existing automations or integrations",
},
"additional_notes": {
"type": "string",
"description": "Any other relevant context or notes",
},
},
"required": [],
}
@property
def requires_auth(self) -> bool:
"""Requires authentication to store user-specific data."""
return True
async def _execute(
self,
user_id: str | None,
session: ChatSession,
**kwargs,
) -> ToolResponseBase:
"""
Capture and store business understanding incrementally.
Each call merges new data with existing understanding:
- String fields are overwritten if provided
- List fields are appended (with deduplication)
"""
session_id = session.session_id
if not user_id:
return ErrorResponse(
message="Authentication required to save business understanding.",
session_id=session_id,
)
# Check if any data was provided
if not any(v is not None for v in kwargs.values()):
return ErrorResponse(
message="Please provide at least one field to update.",
session_id=session_id,
)
# Build input model
input_data = BusinessUnderstandingInput(
user_name=kwargs.get("user_name"),
job_title=kwargs.get("job_title"),
business_name=kwargs.get("business_name"),
industry=kwargs.get("industry"),
business_size=kwargs.get("business_size"),
user_role=kwargs.get("user_role"),
key_workflows=kwargs.get("key_workflows"),
daily_activities=kwargs.get("daily_activities"),
pain_points=kwargs.get("pain_points"),
bottlenecks=kwargs.get("bottlenecks"),
manual_tasks=kwargs.get("manual_tasks"),
automation_goals=kwargs.get("automation_goals"),
current_software=kwargs.get("current_software"),
existing_automation=kwargs.get("existing_automation"),
additional_notes=kwargs.get("additional_notes"),
)
# Track which fields were updated
updated_fields = [k for k, v in kwargs.items() if v is not None]
# Upsert with merge
understanding = await upsert_business_understanding(user_id, input_data)
# Build current understanding summary for the response
current_understanding = {
"user_name": understanding.user_name,
"job_title": understanding.job_title,
"business_name": understanding.business_name,
"industry": understanding.industry,
"business_size": understanding.business_size,
"user_role": understanding.user_role,
"key_workflows": understanding.key_workflows,
"daily_activities": understanding.daily_activities,
"pain_points": understanding.pain_points,
"bottlenecks": understanding.bottlenecks,
"manual_tasks": understanding.manual_tasks,
"automation_goals": understanding.automation_goals,
"current_software": understanding.current_software,
"existing_automation": understanding.existing_automation,
"additional_notes": understanding.additional_notes,
}
# Filter out empty values for cleaner response
current_understanding = {
k: v
for k, v in current_understanding.items()
if v is not None and v != [] and v != ""
}
return UnderstandingUpdatedResponse(
message=f"Updated understanding with: {', '.join(updated_fields)}. "
"I now have a better picture of your business context.",
session_id=session_id,
updated_fields=updated_fields,
current_understanding=current_understanding,
)

View File

@@ -0,0 +1,429 @@
"""Data models and access layer for user business understanding."""
import logging
from datetime import datetime
from typing import Any, Optional, cast
import pydantic
from prisma.models import UserBusinessUnderstanding
from prisma.types import (
UserBusinessUnderstandingCreateInput,
UserBusinessUnderstandingUpdateInput,
)
from backend.data.redis_client import get_redis_async
from backend.util.json import SafeJson
logger = logging.getLogger(__name__)
# Cache configuration
CACHE_KEY_PREFIX = "understanding"
CACHE_TTL_SECONDS = 48 * 60 * 60 # 48 hours
def _cache_key(user_id: str) -> str:
"""Generate cache key for user business understanding."""
return f"{CACHE_KEY_PREFIX}:{user_id}"
def _json_to_list(value: Any) -> list[str]:
"""Convert Json field to list[str], handling None."""
if value is None:
return []
if isinstance(value, list):
return cast(list[str], value)
return []
class BusinessUnderstandingInput(pydantic.BaseModel):
"""Input model for updating business understanding - all fields optional for incremental updates."""
# User info
user_name: Optional[str] = pydantic.Field(None, description="The user's name")
job_title: Optional[str] = pydantic.Field(None, description="The user's job title")
# Business basics
business_name: Optional[str] = pydantic.Field(
None, description="Name of the user's business"
)
industry: Optional[str] = pydantic.Field(None, description="Industry or sector")
business_size: Optional[str] = pydantic.Field(
None, description="Company size (e.g., '1-10', '11-50')"
)
user_role: Optional[str] = pydantic.Field(
None,
description="User's role in the organization (e.g., 'decision maker', 'implementer')",
)
# Processes & activities
key_workflows: Optional[list[str]] = pydantic.Field(
None, description="Key business workflows"
)
daily_activities: Optional[list[str]] = pydantic.Field(
None, description="Daily activities performed"
)
# Pain points & goals
pain_points: Optional[list[str]] = pydantic.Field(
None, description="Current pain points"
)
bottlenecks: Optional[list[str]] = pydantic.Field(
None, description="Process bottlenecks"
)
manual_tasks: Optional[list[str]] = pydantic.Field(
None, description="Manual/repetitive tasks"
)
automation_goals: Optional[list[str]] = pydantic.Field(
None, description="Desired automation goals"
)
# Current tools
current_software: Optional[list[str]] = pydantic.Field(
None, description="Software/tools currently used"
)
existing_automation: Optional[list[str]] = pydantic.Field(
None, description="Existing automations"
)
# Additional context
additional_notes: Optional[str] = pydantic.Field(
None, description="Any additional context"
)
class BusinessUnderstanding(pydantic.BaseModel):
"""Full business understanding model returned from database."""
id: str
user_id: str
created_at: datetime
updated_at: datetime
# User info
user_name: Optional[str] = None
job_title: Optional[str] = None
# Business basics
business_name: Optional[str] = None
industry: Optional[str] = None
business_size: Optional[str] = None
user_role: Optional[str] = None
# Processes & activities
key_workflows: list[str] = pydantic.Field(default_factory=list)
daily_activities: list[str] = pydantic.Field(default_factory=list)
# Pain points & goals
pain_points: list[str] = pydantic.Field(default_factory=list)
bottlenecks: list[str] = pydantic.Field(default_factory=list)
manual_tasks: list[str] = pydantic.Field(default_factory=list)
automation_goals: list[str] = pydantic.Field(default_factory=list)
# Current tools
current_software: list[str] = pydantic.Field(default_factory=list)
existing_automation: list[str] = pydantic.Field(default_factory=list)
# Additional context
additional_notes: Optional[str] = None
@classmethod
def from_db(cls, db_record: UserBusinessUnderstanding) -> "BusinessUnderstanding":
"""Convert database record to Pydantic model."""
return cls(
id=db_record.id,
user_id=db_record.userId,
created_at=db_record.createdAt,
updated_at=db_record.updatedAt,
user_name=db_record.userName,
job_title=db_record.jobTitle,
business_name=db_record.businessName,
industry=db_record.industry,
business_size=db_record.businessSize,
user_role=db_record.userRole,
key_workflows=_json_to_list(db_record.keyWorkflows),
daily_activities=_json_to_list(db_record.dailyActivities),
pain_points=_json_to_list(db_record.painPoints),
bottlenecks=_json_to_list(db_record.bottlenecks),
manual_tasks=_json_to_list(db_record.manualTasks),
automation_goals=_json_to_list(db_record.automationGoals),
current_software=_json_to_list(db_record.currentSoftware),
existing_automation=_json_to_list(db_record.existingAutomation),
additional_notes=db_record.additionalNotes,
)
def _merge_lists(existing: list | None, new: list | None) -> list | None:
"""Merge two lists, removing duplicates while preserving order."""
if new is None:
return existing
if existing is None:
return new
# Preserve order, add new items that don't exist
merged = list(existing)
for item in new:
if item not in merged:
merged.append(item)
return merged
async def _get_from_cache(user_id: str) -> Optional[BusinessUnderstanding]:
"""Get business understanding from Redis cache."""
try:
redis = await get_redis_async()
cached_data = await redis.get(_cache_key(user_id))
if cached_data:
return BusinessUnderstanding.model_validate_json(cached_data)
except Exception as e:
logger.warning(f"Failed to get understanding from cache: {e}")
return None
async def _set_cache(user_id: str, understanding: BusinessUnderstanding) -> None:
"""Set business understanding in Redis cache with TTL."""
try:
redis = await get_redis_async()
await redis.setex(
_cache_key(user_id),
CACHE_TTL_SECONDS,
understanding.model_dump_json(),
)
except Exception as e:
logger.warning(f"Failed to set understanding in cache: {e}")
async def _delete_cache(user_id: str) -> None:
"""Delete business understanding from Redis cache."""
try:
redis = await get_redis_async()
await redis.delete(_cache_key(user_id))
except Exception as e:
logger.warning(f"Failed to delete understanding from cache: {e}")
async def get_business_understanding(
user_id: str,
) -> Optional[BusinessUnderstanding]:
"""Get the business understanding for a user.
Checks cache first, falls back to database if not cached.
Results are cached for 48 hours.
"""
# Try cache first
cached = await _get_from_cache(user_id)
if cached:
logger.debug(f"Business understanding cache hit for user {user_id}")
return cached
# Cache miss - load from database
logger.debug(f"Business understanding cache miss for user {user_id}")
record = await UserBusinessUnderstanding.prisma().find_unique(
where={"userId": user_id}
)
if record is None:
return None
understanding = BusinessUnderstanding.from_db(record)
# Store in cache for next time
await _set_cache(user_id, understanding)
return understanding
async def upsert_business_understanding(
user_id: str,
data: BusinessUnderstandingInput,
) -> BusinessUnderstanding:
"""
Create or update business understanding with incremental merge strategy.
- String fields: new value overwrites if provided (not None)
- List fields: new items are appended to existing (deduplicated)
"""
# Get existing record for merge
existing = await UserBusinessUnderstanding.prisma().find_unique(
where={"userId": user_id}
)
# Build update data with merge strategy
update_data: UserBusinessUnderstandingUpdateInput = {}
create_data: dict[str, Any] = {"userId": user_id}
# String fields - overwrite if provided
if data.user_name is not None:
update_data["userName"] = data.user_name
create_data["userName"] = data.user_name
if data.job_title is not None:
update_data["jobTitle"] = data.job_title
create_data["jobTitle"] = data.job_title
if data.business_name is not None:
update_data["businessName"] = data.business_name
create_data["businessName"] = data.business_name
if data.industry is not None:
update_data["industry"] = data.industry
create_data["industry"] = data.industry
if data.business_size is not None:
update_data["businessSize"] = data.business_size
create_data["businessSize"] = data.business_size
if data.user_role is not None:
update_data["userRole"] = data.user_role
create_data["userRole"] = data.user_role
if data.additional_notes is not None:
update_data["additionalNotes"] = data.additional_notes
create_data["additionalNotes"] = data.additional_notes
# List fields - merge with existing
if data.key_workflows is not None:
existing_list = _json_to_list(existing.keyWorkflows) if existing else None
merged = _merge_lists(existing_list, data.key_workflows)
update_data["keyWorkflows"] = SafeJson(merged)
create_data["keyWorkflows"] = SafeJson(merged)
if data.daily_activities is not None:
existing_list = _json_to_list(existing.dailyActivities) if existing else None
merged = _merge_lists(existing_list, data.daily_activities)
update_data["dailyActivities"] = SafeJson(merged)
create_data["dailyActivities"] = SafeJson(merged)
if data.pain_points is not None:
existing_list = _json_to_list(existing.painPoints) if existing else None
merged = _merge_lists(existing_list, data.pain_points)
update_data["painPoints"] = SafeJson(merged)
create_data["painPoints"] = SafeJson(merged)
if data.bottlenecks is not None:
existing_list = _json_to_list(existing.bottlenecks) if existing else None
merged = _merge_lists(existing_list, data.bottlenecks)
update_data["bottlenecks"] = SafeJson(merged)
create_data["bottlenecks"] = SafeJson(merged)
if data.manual_tasks is not None:
existing_list = _json_to_list(existing.manualTasks) if existing else None
merged = _merge_lists(existing_list, data.manual_tasks)
update_data["manualTasks"] = SafeJson(merged)
create_data["manualTasks"] = SafeJson(merged)
if data.automation_goals is not None:
existing_list = _json_to_list(existing.automationGoals) if existing else None
merged = _merge_lists(existing_list, data.automation_goals)
update_data["automationGoals"] = SafeJson(merged)
create_data["automationGoals"] = SafeJson(merged)
if data.current_software is not None:
existing_list = _json_to_list(existing.currentSoftware) if existing else None
merged = _merge_lists(existing_list, data.current_software)
update_data["currentSoftware"] = SafeJson(merged)
create_data["currentSoftware"] = SafeJson(merged)
if data.existing_automation is not None:
existing_list = _json_to_list(existing.existingAutomation) if existing else None
merged = _merge_lists(existing_list, data.existing_automation)
update_data["existingAutomation"] = SafeJson(merged)
create_data["existingAutomation"] = SafeJson(merged)
# Upsert
record = await UserBusinessUnderstanding.prisma().upsert(
where={"userId": user_id},
data={
"create": UserBusinessUnderstandingCreateInput(**create_data),
"update": update_data,
},
)
understanding = BusinessUnderstanding.from_db(record)
# Update cache with new understanding
await _set_cache(user_id, understanding)
return understanding
async def clear_business_understanding(user_id: str) -> bool:
"""Clear/delete business understanding for a user from both DB and cache."""
# Delete from cache first
await _delete_cache(user_id)
try:
await UserBusinessUnderstanding.prisma().delete(where={"userId": user_id})
return True
except Exception:
# Record might not exist
return False
def format_understanding_for_prompt(understanding: BusinessUnderstanding) -> str:
"""Format business understanding as text for system prompt injection."""
sections = []
# User info section
user_info = []
if understanding.user_name:
user_info.append(f"Name: {understanding.user_name}")
if understanding.job_title:
user_info.append(f"Job Title: {understanding.job_title}")
if user_info:
sections.append("## User\n" + "\n".join(user_info))
# Business section
business_info = []
if understanding.business_name:
business_info.append(f"Company: {understanding.business_name}")
if understanding.industry:
business_info.append(f"Industry: {understanding.industry}")
if understanding.business_size:
business_info.append(f"Size: {understanding.business_size}")
if understanding.user_role:
business_info.append(f"Role Context: {understanding.user_role}")
if business_info:
sections.append("## Business\n" + "\n".join(business_info))
# Processes section
processes = []
if understanding.key_workflows:
processes.append(f"Key Workflows: {', '.join(understanding.key_workflows)}")
if understanding.daily_activities:
processes.append(
f"Daily Activities: {', '.join(understanding.daily_activities)}"
)
if processes:
sections.append("## Processes\n" + "\n".join(processes))
# Pain points section
pain_points = []
if understanding.pain_points:
pain_points.append(f"Pain Points: {', '.join(understanding.pain_points)}")
if understanding.bottlenecks:
pain_points.append(f"Bottlenecks: {', '.join(understanding.bottlenecks)}")
if understanding.manual_tasks:
pain_points.append(f"Manual Tasks: {', '.join(understanding.manual_tasks)}")
if pain_points:
sections.append("## Pain Points\n" + "\n".join(pain_points))
# Goals section
if understanding.automation_goals:
sections.append(
"## Automation Goals\n"
+ "\n".join(f"- {goal}" for goal in understanding.automation_goals)
)
# Current tools section
tools_info = []
if understanding.current_software:
tools_info.append(
f"Current Software: {', '.join(understanding.current_software)}"
)
if understanding.existing_automation:
tools_info.append(
f"Existing Automation: {', '.join(understanding.existing_automation)}"
)
if tools_info:
sections.append("## Current Tools\n" + "\n".join(tools_info))
# Additional notes
if understanding.additional_notes:
sections.append(f"## Additional Context\n{understanding.additional_notes}")
if not sections:
return ""
return "# User Business Context\n\n" + "\n\n".join(sections)

View File

@@ -53,6 +53,7 @@ model User {
Profile Profile[]
UserOnboarding UserOnboarding?
BusinessUnderstanding UserBusinessUnderstanding?
BuilderSearchHistory BuilderSearchHistory[]
StoreListings StoreListing[]
StoreListingReviews StoreListingReview[]
@@ -121,19 +122,109 @@ model UserOnboarding {
User User @relation(fields: [userId], references: [id], onDelete: Cascade)
}
model UserBusinessUnderstanding {
id String @id @default(uuid())
createdAt DateTime @default(now())
updatedAt DateTime @default(now()) @updatedAt
userId String @unique
User User @relation(fields: [userId], references: [id], onDelete: Cascade)
// User info
userName String?
jobTitle String?
// Business basics (string columns)
businessName String?
industry String?
businessSize String? // "1-10", "11-50", "51-200", "201-1000", "1000+"
userRole String? // Role in organization context (e.g., "decision maker", "implementer")
// Processes & activities (JSON arrays)
keyWorkflows Json?
dailyActivities Json?
// Pain points & goals (JSON arrays)
painPoints Json?
bottlenecks Json?
manualTasks Json?
automationGoals Json?
// Current tools (JSON arrays)
currentSoftware Json?
existingAutomation Json?
additionalNotes String?
@@index([userId])
}
model BuilderSearchHistory {
id String @id @default(uuid())
createdAt DateTime @default(now())
updatedAt DateTime @default(now()) @updatedAt
searchQuery String
filter String[] @default([])
byCreator String[] @default([])
filter String[] @default([])
byCreator String[] @default([])
userId String
User User @relation(fields: [userId], references: [id], onDelete: Cascade)
}
////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////
//////////////// CHAT SESSION TABLES ///////////////////
////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////
model ChatSession {
id String @id @default(uuid())
createdAt DateTime @default(now())
updatedAt DateTime @default(now()) @updatedAt
userId String?
// Session metadata
title String?
credentials Json @default("{}") // Map of provider -> credential metadata
// Rate limiting counters (stored as JSON maps)
successfulAgentRuns Json @default("{}") // Map of graph_id -> count
successfulAgentSchedules Json @default("{}") // Map of graph_id -> count
// Usage tracking
totalPromptTokens Int @default(0)
totalCompletionTokens Int @default(0)
Messages ChatMessage[]
@@index([userId, updatedAt])
}
model ChatMessage {
id String @id @default(uuid())
createdAt DateTime @default(now())
sessionId String
Session ChatSession @relation(fields: [sessionId], references: [id], onDelete: Cascade)
// Message content
role String // "user", "assistant", "system", "tool", "function"
content String?
name String?
toolCallId String?
refusal String?
toolCalls Json? // List of tool calls for assistant messages
functionCall Json? // Deprecated but kept for compatibility
// Ordering within session
sequence Int
@@unique([sessionId, sequence])
@@index([sessionId, sequence])
}
// This model describes the Agent Graph/Flow (Multi Agent System).
model AgentGraph {
id String @default(uuid())
@@ -721,26 +812,26 @@ view StoreAgent {
storeListingVersionId String
updated_at DateTime
slug String
agent_name String
agent_video String?
agent_output_demo String?
agent_image String[]
slug String
agent_name String
agent_video String?
agent_output_demo String?
agent_image String[]
featured Boolean @default(false)
creator_username String?
creator_avatar String?
sub_heading String
description String
categories String[]
search Unsupported("tsvector")? @default(dbgenerated("''::tsvector"))
runs Int
rating Float
versions String[]
agentGraphVersions String[]
agentGraphId String
is_available Boolean @default(true)
useForOnboarding Boolean @default(false)
featured Boolean @default(false)
creator_username String?
creator_avatar String?
sub_heading String
description String
categories String[]
search Unsupported("tsvector")? @default(dbgenerated("''::tsvector"))
runs Int
rating Float
versions String[]
agentGraphVersions String[]
agentGraphId String
is_available Boolean @default(true)
useForOnboarding Boolean @default(false)
// Materialized views used (refreshed every 15 minutes via pg_cron):
// - mv_agent_run_counts - Pre-aggregated agent execution counts by agentGraphId
@@ -856,14 +947,14 @@ model StoreListingVersion {
AgentGraph AgentGraph @relation(fields: [agentGraphId, agentGraphVersion], references: [id, version])
// Content fields
name String
subHeading String
videoUrl String?
agentOutputDemoUrl String?
imageUrls String[]
description String
instructions String?
categories String[]
name String
subHeading String
videoUrl String?
agentOutputDemoUrl String?
imageUrls String[]
description String
instructions String?
categories String[]
isFeatured Boolean @default(false)
@@ -899,7 +990,6 @@ model StoreListingVersion {
// Reviews for this specific version
Reviews StoreListingReview[]
@@unique([storeListingId, version])
@@index([storeListingId, submissionStatus, isAvailable])
@@index([submissionStatus])
@@index([reviewerId])
@@ -998,16 +1088,16 @@ model OAuthApplication {
updatedAt DateTime @updatedAt
// Application metadata
name String
description String?
logoUrl String? // URL to app logo stored in GCS
clientId String @unique
clientSecret String // Hashed with Scrypt (same as API keys)
clientSecretSalt String // Salt for Scrypt hashing
name String
description String?
logoUrl String? // URL to app logo stored in GCS
clientId String @unique
clientSecret String // Hashed with Scrypt (same as API keys)
clientSecretSalt String // Salt for Scrypt hashing
// OAuth configuration
redirectUris String[] // Allowed callback URLs
grantTypes String[] @default(["authorization_code", "refresh_token"])
grantTypes String[] @default(["authorization_code", "refresh_token"])
scopes APIKeyPermission[] // Which permissions the app can request
// Application management